Slope coefficients in rank-rank regressions are popular measures of intergenerational mobility, for instance in regressions of a child's income rank on their parent's income rank. In this paper, we first point out that commonly used variance estimators such as the homoskedastic or robust...

We consider estimation and inference for a regression coefficient in panels with interactive fixed effects (i.e., with a factor structure). We show that previously developed estimators and confidence intervals (CIs) might be heavily biased and size-distorted when some of the factors are weak. We...

Given data on a scalar random variable 𝑌, a prediction set for 𝑌 with miscoverage level 𝛼 is a set of values for 𝑌 that contains a randomly drawn 𝑌 with probability 1 - 𝛼, where 𝛼 ∈ (0, 1). Among all prediction sets that satisfy this coverage property, the oracle...

Applying a method suggested by Woodruff (1971), we derive the sampling variances of Generalized Entropy and Atkinson inequality indices when estimated from complex survey data. It turns out that this method also greatly simpli?es the calculations for the i.i.d. case when compared to previous...

Applying a method suggested by Woodruff (1971), we derive the sampling variances of Generalized Entropy and Atkinson inequality indices when estimated from complex survey data. It turns out that this method also greatly simplifies the calculations for the i.i.d. case when compared to previous...

In this article we examine how model selection in neural networks can be guided by statistical procedures such as hypotheses tests, information criteria and cross validation. The application of these methods in neural network models is discussed, paying attention especially to the identification...

This paper investigates the long run and short run relationships of monetary policy, inflation and economic growth in Pakistan using co-integration and causality analysis during the period 0f 1972-2010. A large number of empirical studies on the relationships of monetary policy and inflation are...

In this paper, the regression discontinuity design (RDD) is generalized to account for differences in observed covariates X in a fully nonparametric way. It is shown that the treatment effect can be estimated at the rate for one-dimensional nonparametric regression irrespective of the dimension...

This paper proposes sequential matching and inverse selection probability weighting to estimate dynamic causal effects. The sequential matching estimators extend simple, matching estimators based on propensity scores for static causal analysis that have been frequently applied in the evaluation...

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