A relatively simple frequency-type testing procedure for unit root potentially contaminated by an additive stationary noise is introduced, which encompasses general settings and allows for linear trends. The proposed test for unit root versus stationarity is based on a finite number of...

Granger and Sims non-causality (GSNC) are compared to non-causality based on concepts popular in the microeconometrics and programme evaluation literature (potential outcome non-causality, PONC). GSNC is defined as a set of restrictions on joint distributions of random variables with observable...

I discuss nonlinear difference-in-differences models, arguing their interpretation depends on the context of their application. When parallel trends are assumed in the natural scale of the dependent variable, I contend the treatment effect is the interaction effect (a cross-difference), while if...

This paper investigates the estimation and inference of spatial panel data models in which the regression coefficient vector is a trending function. We use time differences to eliminate the individual effects and employ GMM estimations for regression coefficients with both linear and quadratic...

We provide an overview of recent empirical research on patterns of cross-country growth. The new empirical regularities considered differ from earlier ones, e.g., the well-known Kaldor stylized facts. The new research no longer makes production function accounting a central part of the analysis....

This chapter presents a unified set of estimation methods for fitting a rich array of models describing dynamic relationships within a longitudinal data setting. The discussion surveys approaches for characterizing the micro dynamics of continuous dependent variables both over time and across...

One of the perceived advantages of difference-in-differences (DiD) methods is that they do not explicitly restrict how units select into treatment. However, when justifying DiD, researchers often argue that the treatment is "quasi-randomly" assigned. We investigate what selection mechanisms are...

A space-time filter structure is introduced that can be used to accommodate dependence across space and time in the error components of panel data models that contain random effects. This general specification encompasses several more specific space-time structures that have been used recently...

We propose a new algorithm for estimating treatment effects in contexts where the exogenous variation comes from aggregate time-series shocks. Our estimator combines data-driven unit-level weights with a time-series model. We use the unit weights to control for unobserved aggregate confounders...

We use real-time annual data on the fiscal balance, government current spending, current revenues and net capital outlays as published at a half yearly frequency in the OECD Economic Outlook for 25 OECD countries. For each fiscal year t we have a number of forecasts, a first release, and...