We propose two new procedures for comparing the mean squared prediction error (MSPE) of a benchmark model to the MSPEs of a small set of alternative models that nest the benchmark. Our procedures compare the benchmark to all the alternative models simultaneously rather than sequentially, and do...

Researchers have increasingly realized the need to account for within-group dependence in estimating standard errors of regression parameter estimates. The usual solution is to calculate cluster-robust standard errors that permit heteroskedasticity and within-cluster error correlation, but...

This paper considers the problem of assessing the distributional consequences of a treatment on some outcome variable of interest when treatment intake is (possibly) non-randomized but there is a binary instrument available for the researcher. Such scenario is common in observational studies and...

The bootstrap, introduced by Efron (1982), has become a very popular method for estimating variances and constructing confidence intervals. A key insight is that one can approximate the properties of estimators by using the empirical distribution function of the sample as an approximation for...

Empirical researchers frequently rely on normal approximations in order to summarize and communicate uncertainty about their findings to their scientific audience. When such approximations are unreliable, they can lead the audience to make misguided decisions. We propose to measure the failure...

This paper introduces a simple and tractable sieve estimation of semiparametric conditional factor models with latent factors. We establish large-N-asymptotic properties of the estimators without requiring large T. We also develop a simple bootstrap procedure for conducting inference about the...

In recent years, measured TFP growth in the US has declined. We argue that two forces contributed to this decline: the mismeasurement of intangible capital, and rising markups. Markups affect input shares, while intangibles omitted from measures of investment affect measured capital growth, each...

How does the sustainable level of consumption depend on productivity growth and the size and growth rate of the population? What is the effect of uncertainty over these growth rates? I address these questions using a model in which productivity and population growth are stochastic, and social...

Growth theory is based on the assumption of exponential total factor productivity (TFP) growth. Across countries and time periods I find that TFP growth is actually linear. Unlike the exponential model, the additive growth model provides useful medium-term forecasts of TFP. It also explains the...