Working Paper |
File Downloads |
Abstract Views |
Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
Arellano-bond lasso estimator for dynamic linear panel models |
0 |
0 |
2 |
2 |
0 |
1 |
16 |
19 |
Average and Quantile Effects in Nonseparable Panel Models |
0 |
0 |
0 |
6 |
1 |
1 |
1 |
35 |
Bias Correction in Panel Data Models with Individual Specific Parameters |
0 |
0 |
0 |
41 |
0 |
1 |
3 |
200 |
Bias Corrections for Two-Step Fixed Effects Panel Data Estimators |
0 |
0 |
0 |
408 |
0 |
0 |
3 |
1,538 |
Bias Corrections for Two-Step Fixed Effects Panel Data Estimators |
0 |
0 |
0 |
190 |
1 |
1 |
5 |
670 |
Bias corrections for two-step fixed effects panel data estimators |
0 |
0 |
0 |
253 |
0 |
0 |
2 |
726 |
Censored Quantile Instrumental Variable Estimation via Control Functions |
0 |
0 |
0 |
40 |
0 |
0 |
1 |
178 |
Censored Quantile Instrumental Variable Estimation with Stata |
0 |
0 |
0 |
7 |
0 |
0 |
2 |
63 |
Censored Quantile Instrumental Variable Estimation with Stata |
0 |
0 |
1 |
14 |
0 |
1 |
3 |
102 |
Conditional Rank-Rank Regression |
0 |
0 |
1 |
1 |
2 |
6 |
8 |
8 |
Conditional quantile processes based on series or many regressors |
0 |
0 |
1 |
4 |
0 |
0 |
3 |
8 |
Conditional quantile processes based on series or many regressors |
0 |
0 |
0 |
15 |
2 |
3 |
5 |
53 |
Conditional quantile processes based on series or many regressors |
0 |
0 |
1 |
49 |
0 |
1 |
3 |
114 |
Counterfactual analysis in R: a vignette |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
13 |
Counterfactual analysis in R: a vignette |
0 |
0 |
0 |
53 |
0 |
1 |
2 |
223 |
Decomposing Changes in the Distribution of Real Hourly Wages in the U.S |
1 |
1 |
1 |
5 |
1 |
2 |
4 |
30 |
Decomposing Real Wage Changes in the United States |
0 |
0 |
0 |
15 |
0 |
0 |
2 |
46 |
Distribution Regression Difference-in-Differences |
0 |
0 |
2 |
2 |
1 |
3 |
11 |
11 |
Distribution regression with sample selection and UK wage decomposition |
0 |
0 |
6 |
38 |
2 |
5 |
24 |
57 |
Distribution regression with sample selection, with an application to wage decompositions in the UK |
0 |
0 |
0 |
2 |
0 |
2 |
4 |
41 |
Dynamic Heterogeneous Distribution Regression Panel Models, with an Application to Labor Income Processes |
0 |
0 |
1 |
16 |
0 |
0 |
1 |
17 |
Dynamic Heterogeneous Distribution Regression Panel Models, with an Application to Labor Income Processes |
0 |
0 |
0 |
7 |
0 |
2 |
2 |
12 |
Estimation of Structural Parameters and Marginal Effects in Binary Choice Panel Data Models with Fixed Effects |
0 |
0 |
0 |
141 |
0 |
0 |
3 |
588 |
Evaluating the Role of Individual Specific Heterogeneity in the Relationship Between Subjective Health Assessments and Income |
0 |
0 |
0 |
46 |
0 |
0 |
1 |
122 |
ExtrapoLATE-ing: External Validity and Overidentification in the LATE Framework |
0 |
1 |
4 |
172 |
2 |
3 |
10 |
550 |
Extremal quantile regression: an overview |
0 |
0 |
1 |
7 |
0 |
1 |
4 |
43 |
Extremal quantile regression: an overview |
0 |
0 |
2 |
2 |
0 |
0 |
3 |
5 |
Fischer-Schultz Lecture: Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments, with an Application to Immunization in India |
0 |
0 |
0 |
1 |
7 |
12 |
21 |
123 |
Fisher-Schultz Lecture: Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments, with an Application to Immunization in India |
0 |
1 |
16 |
251 |
34 |
43 |
126 |
768 |
Fixed Effects Estimation of Structural Parameters and Marginal Effects in Panel Probit Models |
0 |
0 |
0 |
179 |
0 |
0 |
4 |
641 |
Fixed effect estimation of large T panel data models |
0 |
0 |
1 |
24 |
1 |
1 |
2 |
129 |
Fixed effect estimation of large T panel data models |
0 |
0 |
0 |
9 |
0 |
1 |
2 |
37 |
Fixed effect estimation of large T panel data models |
0 |
1 |
1 |
2 |
0 |
1 |
2 |
4 |
Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes |
0 |
0 |
1 |
8 |
0 |
0 |
2 |
21 |
Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes |
0 |
0 |
1 |
60 |
0 |
0 |
3 |
104 |
Generic Machine Learning Inference on Heterogeneous Treatment Effects in Randomized Experiments, with an Application to Immunization in India |
0 |
0 |
2 |
96 |
1 |
3 |
11 |
309 |
Generic inference on quantile and quantile effect functions for discrete outcomes |
0 |
0 |
0 |
4 |
0 |
0 |
1 |
39 |
Generic inference on quantile and quantile effect functions for discrete outcomes |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
3 |
Generic inference on quantile and quantile effect functions for discrete outcomes |
0 |
0 |
0 |
5 |
2 |
2 |
3 |
53 |
Generic inference on quantile and quantile effect functions for discrete outcomes |
0 |
0 |
0 |
0 |
0 |
1 |
3 |
4 |
Generic machine learning inference on heterogenous treatment effects in randomized experiments |
0 |
0 |
4 |
63 |
2 |
5 |
15 |
127 |
Generic machine learning inference on heterogenous treatment effects in randomized experiments |
0 |
0 |
1 |
3 |
3 |
5 |
18 |
41 |
Hours Worked and the U.S. Distribution of Real Annual Earnings 1976–2016 |
0 |
0 |
0 |
18 |
0 |
0 |
0 |
46 |
IMPROVING ESTIMATES OF MONOTONE FUNCTIONS BY REARRANGEMENT |
0 |
0 |
0 |
39 |
0 |
1 |
1 |
150 |
INFERENCE ON COUNTERFACTUAL DISTRIBUTIONS |
0 |
0 |
0 |
108 |
1 |
1 |
3 |
389 |
Identification and Estimation of Marginal Effects in Nonlinear Panel Models |
0 |
0 |
0 |
47 |
1 |
3 |
7 |
179 |
Identification and estimation of marginal effects in nonlinear panel models |
0 |
0 |
1 |
31 |
0 |
0 |
2 |
117 |
Identification and estimation of marginal effects in nonlinear panel models |
0 |
0 |
0 |
106 |
0 |
1 |
3 |
325 |
Improving Estimates of Monotone Functions by Rearrangement |
0 |
0 |
0 |
1 |
0 |
1 |
1 |
17 |
Improving Point and Interval Estimates of Monotone Functions by Rearrangement |
0 |
0 |
0 |
4 |
1 |
1 |
3 |
21 |
Improving estimates of monotone functions by rearrangement |
0 |
0 |
0 |
58 |
0 |
0 |
1 |
227 |
Improving point and interval estimates of monotone functions by rearrangement |
0 |
0 |
0 |
65 |
0 |
0 |
0 |
314 |
Improving point and interval estimators of monotone functions by rearrangement |
0 |
0 |
0 |
0 |
1 |
1 |
2 |
4 |
Improving point and interval estimators of monotone functions by rearrangement |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
Individual and Time Effects in Nonlinear Panel Models with Large N, T |
0 |
1 |
1 |
34 |
0 |
1 |
4 |
173 |
Individual and time effects in nonlinear panel models with large N, T |
0 |
0 |
0 |
0 |
1 |
1 |
2 |
4 |
Individual and time effects in nonlinear panel models with large N, T |
0 |
0 |
0 |
45 |
0 |
0 |
3 |
105 |
Individual and time effects in nonlinear panel models with large N, T |
0 |
0 |
0 |
20 |
0 |
0 |
1 |
92 |
Individual and time effects in nonlinear panel models with large N, T |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
3 |
Individual and time effects in nonlinear panel models with large N, T |
0 |
0 |
0 |
0 |
1 |
1 |
4 |
5 |
Individual and time effects in nonlinear panel models with large N, T |
0 |
0 |
0 |
7 |
2 |
2 |
3 |
99 |
Inference for Extremal Conditional Quantile Models, with an Application to Market and Birthweight Risks |
0 |
0 |
0 |
5 |
0 |
0 |
1 |
47 |
Inference for extremal conditional quantile models, with an application to market and birthweight risks |
0 |
0 |
0 |
20 |
0 |
0 |
4 |
89 |
Inference on Counterfactual Distributions |
0 |
0 |
2 |
23 |
1 |
3 |
9 |
147 |
Inference on counterfactual distributions |
0 |
0 |
0 |
0 |
1 |
1 |
1 |
2 |
Inference on counterfactual distributions |
0 |
0 |
0 |
434 |
3 |
3 |
3 |
940 |
Inference on counterfactual distributions |
0 |
0 |
0 |
893 |
1 |
2 |
4 |
1,922 |
Inference on counterfactual distributions |
0 |
0 |
0 |
0 |
1 |
1 |
2 |
4 |
Inference on counterfactual distributions |
0 |
0 |
0 |
1 |
1 |
1 |
4 |
5 |
Inference on counterfactual distributions |
0 |
0 |
0 |
113 |
0 |
0 |
2 |
351 |
Low-rank approximations of nonseparable panel models |
0 |
0 |
2 |
4 |
0 |
0 |
4 |
12 |
Low-rank approximations of nonseparable panel models |
0 |
0 |
0 |
1 |
0 |
0 |
3 |
15 |
Marital Sorting, Household Inequality and Selection |
0 |
0 |
0 |
5 |
0 |
1 |
1 |
7 |
Mastering Panel Metrics: Causal Impact of Democracy on Growth |
0 |
0 |
0 |
41 |
0 |
0 |
1 |
40 |
Network and Panel Quantile Effects Via Distribution Regression |
0 |
0 |
0 |
5 |
2 |
2 |
2 |
14 |
Network and panel quantile effects via distribution regression |
0 |
0 |
0 |
11 |
1 |
1 |
2 |
31 |
Network and panel quantile effects via distribution regression |
0 |
0 |
0 |
2 |
1 |
1 |
2 |
24 |
Nonlinear Factor Models for Network and Panel Data |
0 |
0 |
0 |
12 |
1 |
1 |
3 |
58 |
Nonlinear factor models for network and panel data |
0 |
0 |
0 |
28 |
2 |
2 |
3 |
63 |
Nonlinear factor models for network and panel data |
0 |
0 |
0 |
5 |
0 |
1 |
3 |
33 |
Nonparametric Identification in Panels using Quantiles |
0 |
0 |
0 |
1 |
0 |
1 |
1 |
13 |
Nonparametric identification in panels using quantiles |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
Nonparametric identification in panels using quantiles |
0 |
0 |
0 |
12 |
0 |
0 |
1 |
59 |
Nonparametric identification in panels using quantiles |
0 |
0 |
0 |
23 |
0 |
1 |
2 |
40 |
Nonparametric identification in panels using quantiles |
0 |
0 |
0 |
0 |
1 |
1 |
1 |
2 |
Nonseparable Sample Selection Models with Censored Selection Rules |
0 |
0 |
1 |
7 |
0 |
1 |
6 |
64 |
Nonseparable Sample Selection Models with Censored Selection Rules: An Application to Wage Decompositions |
0 |
0 |
0 |
22 |
0 |
0 |
0 |
64 |
Nonseparable multinomial choice models in cross-section and panel data |
0 |
0 |
0 |
15 |
0 |
0 |
0 |
24 |
Nonseparable multinomial choice models in cross-section and panel data |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
3 |
Nonseparable sample selection models with censored selection rules |
0 |
0 |
0 |
4 |
1 |
2 |
3 |
39 |
Panel Data Models with Nonadditive Unobserved Heterogeneity: Estimation and Inference |
0 |
0 |
0 |
110 |
0 |
0 |
2 |
346 |
Panel Data Models with Nonadditive Unobserved Heterogeneity: Estimation and Inference |
0 |
0 |
0 |
5 |
0 |
0 |
0 |
33 |
Program evaluation and causal inference with high-dimensional data |
0 |
0 |
0 |
27 |
0 |
0 |
2 |
121 |
Program evaluation and causal inference with high-dimensional data |
0 |
0 |
0 |
1 |
0 |
1 |
4 |
12 |
Program evaluation with high-dimensional data |
0 |
1 |
1 |
1 |
0 |
1 |
2 |
10 |
Program evaluation with high-dimensional data |
0 |
0 |
0 |
16 |
0 |
0 |
2 |
121 |
Program evaluation with high-dimensional data |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
Program evaluation with high-dimensional data |
0 |
0 |
0 |
11 |
1 |
1 |
5 |
92 |
Program evaluation with high-dimensional data |
0 |
0 |
0 |
75 |
0 |
1 |
1 |
201 |
Program evaluation with high-dimensional data |
0 |
0 |
0 |
0 |
0 |
0 |
4 |
7 |
Program evaluation with high-dimensional data |
0 |
0 |
0 |
5 |
0 |
0 |
2 |
79 |
Program evaluation with high-dimensional data |
0 |
0 |
0 |
0 |
0 |
0 |
3 |
5 |
QUANTILE AND PROBABILITY CURVES WITHOUT CROSSING |
0 |
0 |
0 |
71 |
1 |
2 |
4 |
341 |
Quantile Regression under Misspecification |
0 |
0 |
0 |
2 |
0 |
0 |
6 |
455 |
Quantile Regression under Misspecification, with an Application to the U.S. Wage Structure |
0 |
0 |
2 |
287 |
0 |
1 |
6 |
946 |
Quantile Regression with Censoring and Endogeneity |
0 |
0 |
1 |
112 |
0 |
0 |
2 |
364 |
Quantile Regression with Censoring and Endogeneity |
0 |
0 |
2 |
6 |
0 |
1 |
4 |
111 |
Quantile Regression with Censoring and Endogeneity |
0 |
0 |
1 |
58 |
3 |
5 |
7 |
194 |
Quantile and Average Effects in Nonseparable Panel Models |
0 |
0 |
0 |
25 |
0 |
0 |
0 |
99 |
Quantile and Probability Curves Without Crossing |
0 |
0 |
0 |
3 |
0 |
1 |
2 |
31 |
Quantile and Probability Curves without Crossing |
0 |
0 |
0 |
18 |
2 |
2 |
5 |
143 |
Quantile and Probability Curves without Crossing |
0 |
0 |
1 |
3 |
0 |
0 |
2 |
49 |
Quantile and average effects in nonseparable panel models |
0 |
0 |
0 |
43 |
0 |
0 |
1 |
113 |
Quantile and probability curves without crossing |
0 |
0 |
0 |
68 |
0 |
0 |
1 |
272 |
Quantile regression with censoring and endogeneity |
0 |
0 |
0 |
40 |
1 |
2 |
4 |
141 |
Quantreg.nonpar: an R package for performing nonparametric series quantile regression |
0 |
0 |
0 |
3 |
0 |
0 |
3 |
19 |
Quantreg.nonpar: an R package for performing nonparametric series quantile regression |
0 |
0 |
0 |
19 |
0 |
0 |
1 |
131 |
Rearranging Edgeworth-Cornish-Fisher Expansions |
0 |
0 |
0 |
2 |
1 |
2 |
2 |
17 |
Rearranging Edgeworth-Cornish-Fisher Expansions |
0 |
0 |
0 |
0 |
0 |
0 |
0 |
4 |
Rearranging Edgeworth-Cornish-Fisher Expansions |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
3 |
Rearranging Edgeworth-Cornish-Fisher expansions |
0 |
0 |
0 |
90 |
0 |
0 |
0 |
331 |
Selection and the Distribution of Female Hourly Wages in the U.S |
0 |
0 |
0 |
7 |
0 |
0 |
2 |
17 |
Semiparametric Estimation of Structural Functions in Nonseparable Triangular Models |
0 |
0 |
0 |
20 |
0 |
0 |
0 |
90 |
Semiparametric estimation of structural functions in nonseparable triangular models |
0 |
0 |
0 |
2 |
1 |
1 |
1 |
36 |
Semiparametric estimation of structural functions in nonseparable triangular models |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
The Sorted Effects Method: Discovering Heterogeneous Effects Beyond Their Averages |
0 |
0 |
0 |
15 |
2 |
3 |
8 |
67 |
The sorted effects method: discovering heterogeneous effects beyond their averages |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
7 |
The sorted effects method: discovering heterogeneous effects beyond their averages |
0 |
0 |
0 |
14 |
0 |
0 |
2 |
79 |
probitfe and logitfe: Bias corrections for probit and logit models with two-way fixed effects |
0 |
0 |
1 |
46 |
2 |
3 |
15 |
119 |
Total Working Papers |
1 |
6 |
66 |
5,716 |
101 |
176 |
563 |
19,470 |
Journal Article |
File Downloads |
Abstract Views |
Last month |
3 months |
12 months |
Total |
Last month |
3 months |
12 months |
Total |
Average and Quantile Effects in Nonseparable Panel Models |
0 |
0 |
0 |
38 |
2 |
4 |
7 |
197 |
Bias corrections for probit and logit models with two-way fixed effects |
0 |
0 |
2 |
77 |
0 |
0 |
8 |
296 |
Bias corrections for two-step fixed effects panel data estimators |
0 |
0 |
3 |
164 |
1 |
5 |
13 |
530 |
Censored quantile instrumental-variable estimation with Stata |
0 |
0 |
2 |
12 |
0 |
0 |
3 |
60 |
Conditional quantile processes based on series or many regressors |
0 |
1 |
2 |
39 |
0 |
2 |
6 |
109 |
Evaluating the role of income, state dependence and individual specific heterogeneity in the determination of subjective health assessments |
0 |
0 |
0 |
0 |
0 |
1 |
3 |
18 |
Fast algorithms for the quantile regression process |
1 |
2 |
3 |
7 |
2 |
3 |
10 |
29 |
Fixed Effects Estimation of Large-TPanel Data Models |
0 |
0 |
2 |
19 |
1 |
5 |
19 |
96 |
Fixed effects estimation of structural parameters and marginal effects in panel probit models |
0 |
3 |
9 |
357 |
1 |
10 |
25 |
1,034 |
Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes |
0 |
0 |
1 |
10 |
0 |
0 |
3 |
47 |
Household labor supply: evidence for Spain |
0 |
0 |
0 |
107 |
1 |
1 |
3 |
392 |
Improving point and interval estimators of monotone functions by rearrangement |
0 |
0 |
0 |
34 |
2 |
2 |
5 |
140 |
Individual and time effects in nonlinear panel models with large N, T |
0 |
2 |
15 |
248 |
2 |
11 |
58 |
847 |
Inference for Extremal Conditional Quantile Models, with an Application to Market and Birthweight Risks |
0 |
0 |
1 |
36 |
0 |
3 |
14 |
164 |
Inference on Counterfactual Distributions |
0 |
1 |
2 |
368 |
4 |
8 |
18 |
976 |
Low-rank approximations of nonseparable panel models |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
9 |
Mastering Panel Metrics: Causal Impact of Democracy on Growth |
0 |
1 |
2 |
30 |
1 |
3 |
11 |
93 |
Network and panel quantile effects via distribution regression |
0 |
0 |
2 |
4 |
1 |
1 |
10 |
13 |
Nonlinear factor models for network and panel data |
0 |
0 |
4 |
39 |
1 |
1 |
11 |
111 |
Nonparametric identification in panels using quantiles |
0 |
0 |
0 |
16 |
0 |
1 |
1 |
94 |
Nonseparable multinomial choice models in cross-section and panel data |
0 |
0 |
1 |
13 |
1 |
1 |
5 |
66 |
Nonseparable sample selection models with censored selection rules |
0 |
0 |
0 |
1 |
0 |
0 |
4 |
5 |
Panel data models with nonadditive unobserved heterogeneity: Estimation and inference |
0 |
0 |
0 |
23 |
0 |
0 |
4 |
104 |
Parametric Modeling of Quantile Regression Coefficient Functions With Longitudinal Data |
0 |
1 |
2 |
6 |
0 |
1 |
3 |
16 |
Philip G. Wright, directed acyclic graphs, and instrumental variables |
0 |
0 |
2 |
2 |
0 |
0 |
2 |
2 |
Program Evaluation and Causal Inference With High‐Dimensional Data |
0 |
1 |
2 |
34 |
0 |
3 |
8 |
144 |
Quantile Regression under Misspecification, with an Application to the U.S. Wage Structure |
0 |
0 |
1 |
400 |
0 |
0 |
9 |
1,243 |
Quantile and Probability Curves Without Crossing |
0 |
0 |
0 |
82 |
3 |
3 |
5 |
310 |
Quantile regression with censoring and endogeneity |
0 |
0 |
4 |
89 |
0 |
0 |
13 |
399 |
Rearranging Edgeworth–Cornish–Fisher expansions |
0 |
0 |
0 |
31 |
1 |
2 |
2 |
135 |
Semiparametric estimation of structural functions in nonseparable triangular models |
0 |
0 |
0 |
1 |
1 |
3 |
5 |
29 |
The Consequences of Teenage Childbearing: Consistent Estimates When Abortion Makes Miscarriage Non‐random |
0 |
0 |
0 |
23 |
0 |
1 |
5 |
209 |
The Sorted Effects Method: Discovering Heterogeneous Effects Beyond Their Averages |
1 |
1 |
2 |
18 |
1 |
2 |
7 |
95 |
Total Journal Articles |
2 |
13 |
64 |
2,328 |
26 |
78 |
301 |
8,012 |