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12 months |
Total |
Last month |
3 months |
12 months |
Total |

A contribution to the Reinhart and Rogoff debate: not 90 percent but maybe 30 percent |
2 |
2 |
2 |
29 |
3 |
4 |
7 |
55 |

Ability, sorting and wage inequality |
0 |
0 |
0 |
171 |
0 |
0 |
3 |
530 |

An Econometric Perspective on Algorithmic Subsampling |
0 |
1 |
3 |
25 |
2 |
4 |
16 |
21 |

Best Subset Binary Prediction |
0 |
0 |
0 |
1 |
2 |
2 |
13 |
26 |

Best subset binary prediction |
0 |
0 |
0 |
24 |
0 |
0 |
10 |
41 |

Breaking the curse of dimensionality in conditional moment inequalities for discrete choice models |
0 |
0 |
0 |
7 |
2 |
3 |
14 |
28 |

Breaking the curse of dimensionality in conditional moment inequalities for discrete choice models |
0 |
0 |
0 |
31 |
2 |
3 |
8 |
79 |

Causal Inference in Case-Control Studies |
0 |
0 |
17 |
17 |
2 |
6 |
8 |
8 |

Characterization of the Asymptotic Distribution of Semiparametric M-Estimators |
0 |
0 |
1 |
175 |
1 |
1 |
7 |
372 |

Characterization of the asymptotic distribution of semiparametric M-estimators |
0 |
0 |
1 |
6 |
0 |
1 |
6 |
32 |

Characterization of the asymptotic distribution of semiparametric M-estimators |
0 |
0 |
1 |
142 |
0 |
1 |
7 |
343 |

DOUBLY ROBUST UNIFORM CONFIDENCE BAND FOR THE CONDITIONAL AVERAGE TREATMENT EFFECT FUNCTION |
0 |
1 |
1 |
21 |
0 |
5 |
12 |
73 |

Desperate times call for desperate measures: government spending multipliers in hard times |
0 |
0 |
2 |
2 |
1 |
5 |
14 |
14 |

Desperate times call for desperate measures: government spending multipliers in hard times |
0 |
0 |
17 |
17 |
0 |
0 |
23 |
23 |

Desperate times call for desperate measures: government spending multipliers in hard times |
0 |
0 |
5 |
5 |
1 |
1 |
6 |
6 |

Do Institutions Affect Social Preferences? Evidence from Divided Korea |
0 |
0 |
1 |
83 |
1 |
4 |
15 |
125 |

Do institutions affect social preferences? Evidence from divided Korea |
0 |
0 |
1 |
115 |
1 |
3 |
19 |
146 |

Does It Matter Who Responded to the Survey? Trends in the U.S. Gender Earnings Gap Revisited |
0 |
0 |
0 |
31 |
1 |
1 |
5 |
119 |

Does it matter who responded to the survey? Trends in the U.S. gender earnings gap revisited |
0 |
0 |
0 |
8 |
0 |
0 |
2 |
52 |

Doubly Robust Uniform Confidence Band for the Conditional Average Treatment Effect Function |
0 |
0 |
0 |
2 |
1 |
4 |
6 |
13 |

Doubly robust uniform confidence band for the conditional average treatment effect function |
0 |
0 |
0 |
49 |
1 |
5 |
15 |
130 |

Doubly robust uniform confidence band for the conditional average treatment effect function |
0 |
0 |
0 |
7 |
1 |
5 |
14 |
33 |

Endogeneity in Quantile Regression Models: A Control Function Approach |
1 |
2 |
6 |
528 |
1 |
4 |
21 |
1,607 |

Endogeneity in quantile regression models: a control function approach |
0 |
0 |
1 |
258 |
0 |
0 |
7 |
879 |

Estimating distributions of potential outcomes using local instrumental variables with an application to changes in college enrollment and wage inequality |
0 |
0 |
2 |
134 |
0 |
0 |
4 |
296 |

Estimating panel data duration models with censored data |
0 |
0 |
1 |
276 |
0 |
0 |
4 |
810 |

Exact computation of GMM estimators for instrumental variable quantile regression models |
0 |
0 |
0 |
23 |
1 |
1 |
7 |
25 |

Factor-Driven Two-Regime Regression |
0 |
0 |
9 |
9 |
1 |
7 |
13 |
13 |

Factor-Driven Two-Regime Regression |
0 |
0 |
1 |
4 |
0 |
1 |
20 |
32 |

Factor-Driven Two-Regime Regression |
1 |
2 |
5 |
49 |
3 |
4 |
30 |
62 |

Filtered and Unfiltered Treatment Effects with Targeting Instruments |
0 |
0 |
0 |
0 |
2 |
2 |
2 |
2 |

Filtered and Unfiltered Treatment Effects with Targeting Instruments |
0 |
0 |
0 |
0 |
2 |
2 |
2 |
2 |

High Dimensional Classification through $\ell_0$-Penalized Empirical Risk Minimization |
0 |
0 |
0 |
10 |
0 |
0 |
7 |
25 |

Identification of a competing risks model with unknown transformations of latent failure times |
0 |
0 |
0 |
97 |
0 |
0 |
2 |
389 |

Identifying Effects of Multivalued Treatments |
0 |
0 |
0 |
45 |
5 |
5 |
11 |
56 |

Identifying Effects of Multivalued Treatments |
0 |
0 |
0 |
39 |
0 |
1 |
6 |
27 |

Identifying effects of multivalued treatments |
0 |
0 |
0 |
10 |
2 |
2 |
8 |
23 |

Identifying effects of multivalued treatments |
0 |
0 |
0 |
5 |
2 |
2 |
7 |
18 |

Identifying the Effect of Persuasion |
0 |
0 |
0 |
10 |
2 |
2 |
11 |
17 |

Identifying the effect of persuasion |
0 |
0 |
1 |
2 |
1 |
3 |
14 |
28 |

Implementing intersection bounds in Stata |
0 |
0 |
0 |
24 |
2 |
2 |
12 |
102 |

Implementing intersection bounds in Stata |
0 |
0 |
0 |
7 |
1 |
1 |
7 |
50 |

Institutions, Competitiveness and Cognitive Ability |
4 |
15 |
15 |
15 |
4 |
11 |
11 |
11 |

International trends in technological progress: stylized facts from patent citations, 1980-2011 |
0 |
0 |
1 |
62 |
0 |
0 |
5 |
80 |

Intersection Bounds: estimation and inference |
0 |
0 |
0 |
84 |
1 |
2 |
9 |
313 |

Intersection bounds: estimation and inference |
0 |
0 |
0 |
14 |
0 |
0 |
8 |
86 |

Intersection bounds: estimation and inference |
0 |
0 |
1 |
34 |
0 |
2 |
8 |
112 |

Is Distance Dying at Last? |
0 |
0 |
0 |
1 |
1 |
2 |
8 |
16 |

Is Distance Dying at Last? Falling Home Bias in Fixed Effects Models of Patent Citations |
0 |
0 |
0 |
34 |
2 |
5 |
12 |
150 |

Is Distance Dying at Last? Falling Home Bias in Fixed Effects Models of Patent Citations |
0 |
1 |
1 |
58 |
2 |
4 |
14 |
218 |

Is Distance Dying at Last? Falling Home Bias in Fixed Effects Models of Patent Citations |
0 |
0 |
0 |
65 |
2 |
4 |
14 |
223 |

Is distance dying at last? |
0 |
0 |
0 |
7 |
1 |
1 |
4 |
56 |

Is distance dying at last? Falling home bias in fixed effects models of patent citations |
0 |
0 |
0 |
0 |
1 |
4 |
9 |
60 |

Is distance dying at last? Falling home bias in fixed effects models of patent citations |
0 |
0 |
1 |
50 |
3 |
6 |
14 |
172 |

Is distance dying at last? Falling home bias in fixed effects models of patent citations |
0 |
0 |
0 |
2 |
2 |
4 |
12 |
54 |

Knowledge spillovers and patent citations: trends in geographic localization, 1976-2015 |
0 |
1 |
38 |
38 |
5 |
11 |
25 |
25 |

Knowledge spillovers and patent citations: trends in geographic localization, 1976-2015 |
1 |
4 |
13 |
102 |
2 |
10 |
32 |
107 |

Local Identification of Nonparametric and Semiparametric Models |
0 |
0 |
0 |
12 |
0 |
1 |
11 |
127 |

Local Identification of Nonparametric and Semiparametric Models |
0 |
0 |
0 |
48 |
0 |
1 |
4 |
166 |

Local identification of nonparametric and semiparametric models |
0 |
0 |
0 |
16 |
1 |
2 |
8 |
73 |

Local identification of nonparametric and semiparametric models |
0 |
0 |
1 |
31 |
1 |
3 |
11 |
107 |

Maximum score estimation of preference parameters for a binary choice model under uncertainty |
0 |
0 |
0 |
48 |
2 |
2 |
10 |
148 |

Maximum score estimation with nonparametrically generated regressors |
0 |
2 |
2 |
20 |
1 |
6 |
17 |
68 |

Non-Asymptotic Inference in a Class of Optimization Problems |
0 |
0 |
2 |
16 |
1 |
2 |
9 |
11 |

Nonparametric Estimation of an Additive Quantile Regression Model |
0 |
1 |
1 |
362 |
0 |
6 |
11 |
954 |

Nonparametric Identification of Accelerated Failure Time Competing Risks Models |
0 |
0 |
0 |
40 |
3 |
4 |
9 |
136 |

Nonparametric Tests of Conditional Treatment Effects |
0 |
0 |
5 |
138 |
1 |
6 |
33 |
456 |

Nonparametric estimation and inference under shape restrictions |
0 |
0 |
0 |
1 |
2 |
4 |
9 |
26 |

Nonparametric estimation and inference under shape restrictions |
0 |
0 |
0 |
43 |
2 |
4 |
11 |
80 |

Nonparametric estimation of an additive quantile regression model |
0 |
0 |
1 |
166 |
0 |
2 |
11 |
463 |

Nonparametric identification of accelerated failure time competing risks models |
0 |
0 |
0 |
41 |
2 |
3 |
7 |
121 |

Nonparametric instrumental variables estimation of a quantile regression model |
0 |
0 |
2 |
235 |
0 |
2 |
7 |
658 |

Nonparametric tests of conditional treatment effects |
0 |
0 |
1 |
30 |
0 |
5 |
13 |
133 |

Optimal Data Collection for Randomized Control Trials |
0 |
0 |
0 |
39 |
0 |
1 |
11 |
24 |

Optimal Data Collection for Randomized Control Trials |
0 |
0 |
9 |
9 |
1 |
5 |
17 |
17 |

Optimal Data Collection for Randomized Control Trials |
0 |
0 |
1 |
51 |
0 |
3 |
17 |
65 |

Optimal data collection for randomized control trials |
0 |
0 |
0 |
76 |
1 |
3 |
13 |
30 |

Optimal data collection for randomized control trials |
0 |
0 |
0 |
91 |
0 |
2 |
12 |
34 |

Optimal data collection for randomized control trials |
0 |
0 |
1 |
40 |
2 |
4 |
21 |
37 |

Oracle Estimation of a Change Point in High Dimensional Quantile Regression |
0 |
0 |
0 |
25 |
0 |
0 |
10 |
21 |

Please Call Me John: Name Choice and the Assimilation of Immigrants in the United States, 1900-1930 |
0 |
0 |
2 |
58 |
3 |
6 |
21 |
89 |

Please Call Me John: Name Choice and the Assimilation of Immigrants in the United States, 1900-1930 |
0 |
0 |
0 |
65 |
2 |
4 |
9 |
59 |

Please call me John: name choice and the assimilation of immigrants in the United States, 1900-1930 |
0 |
1 |
2 |
56 |
2 |
6 |
19 |
116 |

Powerful Inference |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |

Property Rights and Fairness: A Tale of Two Koreas |
0 |
1 |
15 |
15 |
0 |
1 |
29 |
29 |

Recombinant innovation and the boundaries of the firm |
0 |
0 |
0 |
16 |
1 |
1 |
13 |
64 |

Reform of Unemployment Compensation in Germany: A Nonparametric Bounds Analysis Using Register Data |
0 |
0 |
0 |
28 |
0 |
2 |
5 |
248 |

Reform of unemployment compensation in Germany: a nonparametric bounds analysis using register data |
0 |
0 |
0 |
82 |
0 |
1 |
5 |
584 |

SEMIPARAMETRIC ESTIMATION OF A BINARYRESPONSE MODEL WITH A CHANGE-POINTDUE TO A COVARIATE THRESHOLD |
0 |
0 |
0 |
4 |
1 |
1 |
4 |
22 |

Semiparametric Estimation of a Panel Data Proportional Hazards Model with Fixed Effects |
0 |
0 |
1 |
507 |
1 |
2 |
7 |
1,317 |

Semiparametric estimation of a binary response model with a change-point due to a covariate threshold |
0 |
0 |
0 |
2 |
1 |
1 |
8 |
41 |

Semiparametric estimation of a panel data proportional hazards model with fixed effects |
0 |
0 |
1 |
279 |
0 |
0 |
3 |
790 |

Sketching for Two-Stage Least Squares Estimation |
4 |
14 |
14 |
14 |
5 |
7 |
7 |
7 |

Sparse HP Filter: Finding Kinks in the COVID-19 Contact Rate |
0 |
2 |
2 |
2 |
4 |
8 |
8 |
8 |

Sparse HP Filter: Finding Kinks in the COVID-19 Contact Rate |
0 |
8 |
8 |
8 |
3 |
18 |
18 |
18 |

Sparse HP Filter: Finding Kinks in the COVID-19 Contact Rate |
1 |
13 |
13 |
13 |
3 |
9 |
9 |
9 |

Sparse Quantile Regression |
0 |
13 |
13 |
13 |
4 |
11 |
11 |
11 |

TESTING FOR A GENERAL CLASS OF FUNCTIONAL INEQUALITIES |
0 |
0 |
0 |
54 |
1 |
1 |
5 |
74 |

TESTING FOR STOCHASTICMONOTONICITY |
0 |
0 |
0 |
0 |
2 |
3 |
11 |
39 |

Testing a parametric quantile-regression model with an endogenous explanatory variable against a nonparametric alternative |
0 |
0 |
0 |
162 |
0 |
0 |
1 |
556 |

Testing for a general class of functional inequalities |
0 |
0 |
0 |
20 |
1 |
2 |
8 |
78 |

Testing for stochastic monotonicity |
0 |
0 |
0 |
1 |
1 |
2 |
10 |
41 |

Testing for stochastic monotonicity |
0 |
0 |
0 |
52 |
1 |
3 |
11 |
146 |

Testing for threshold effects in regression models |
0 |
1 |
3 |
201 |
3 |
6 |
14 |
539 |

Testing functional inequalities |
0 |
0 |
0 |
66 |
0 |
0 |
5 |
127 |

The identification power of smoothness assumptions in models with counterfactual outcomes |
0 |
0 |
0 |
27 |
1 |
2 |
3 |
78 |

The lasso for high-dimensional regression with a possible change-point |
0 |
0 |
0 |
31 |
2 |
6 |
16 |
126 |

Trends in Quality Adjusted Skill Premia in the US, 1960-2000 |
0 |
0 |
0 |
30 |
0 |
0 |
4 |
88 |

Trends in Quality-Adjusted Skill Premia in the United States, 1960-2000 |
0 |
0 |
1 |
85 |
1 |
2 |
4 |
177 |

Trends in quality-adjusted skill premia in the United States, 1960-2000 |
0 |
0 |
0 |
323 |
0 |
0 |
4 |
573 |

Uniform confidence bands for functions estimated nonparametrically with instrumental variables |
0 |
0 |
0 |
71 |
0 |
2 |
6 |
210 |

Uniform confidence bands for functions estimated nonparametrically with instrumental variables |
0 |
0 |
0 |
27 |
1 |
3 |
5 |
66 |

Total Working Papers |
15 |
86 |
250 |
6,955 |
138 |
345 |
1,176 |
18,701 |