The method of covariate adjustment is often used for estimation of total treatment effects from observational studies. Restricting attention to causal linear models, a recent article (Henckel et al., 2019) derived two novel ...

Cooper and Willis (2003) is the latest in a sequence of criticisms of our methodology for estimating aggregate nonlinearities when microeconomic adjustment is lumpy. Their case is based on “reproducing” our main findings ...

Regression models for the mean quality-adjusted survival time are specified from hazard functions of transitions between two states and the mean quality-adjusted survival time may be a complex function of covariates. We ...

The current study aims to evaluate the effectiveness of an intervention based on the Sport Education model, compared to an intervention based on the traditional model of Direct Instruction in children. The intervention was ...

We consider the issue of performing accurate small-sample likelihood-based inference in beta regression models, which are useful for modelling continuous proportions that are affected by independent variables. We derive ...

In this paper we derive a model of aggregate investment that builds from the lumpymicroeconomic behavior of firms facing stochastic fixed adjustment costs. Instead of theŽ.standard sharp S, s bands, firms’ adjustment ...

This paper proposes a model to study how conditional lending and immediate liquidity provision affect incentives for fiscal adjustment in a country facing the risk of sovereign default. Conditional lending provides explicit ...

This article shows, using R software, how to seasonally adjust a time series using the X-13-ARIMA-SEATS program and the seasonal package developed by Christoph Sax. In addition to presenting step-by-step seasonal adjustment, ...

Currently, the electrical system in Argentina is working at its maximum capacity, decreasing the margin between the installed power and demanded consumption, and drastically reducing the service life of transformer substations ...