In this paper, we study the Jarque–Bera (JB) and cusum tests for the normality of innovations and parameter change in BCTT-GARCH models. In order to demonstrate the validity of JB normality and cusum parameter change tests, we derive their limiting null distributions under mild conditions.

I provide the nonparametric identification of nonlinear dynamic panel data models. I relax the assumption of covariate evolution in Shiu and Hu (2013) by the results of Hu and Shum (2012). The assumptions include first-order Markov assumptions and a restriction on the evolution of the covariate.

We used the unobserved component model of Harvey (1989, 2011) to estimate the Phillips curve for the USA and Australia, augmenting it with the oil price. Our results show that while the coefficient of demand pressure and the intercept decreased, the coefficient of the oil price increased....

When estimating location choices, Poisson regressions and conditional logit models yield identical coefficient estimates (Guimarães et al., 2003). These econometric models involve polar assumptions as regards the similarity of the different locations. Schmidheiny and Brülhart (2011)...

In the linear instrumental variables model, we characterize fixed alternatives against which the test of overidentifying restrictions (OR) is inconsistent. When there is the notion of a “true parameter”, we relate this inconsistency result to the literature on optimality properties of...

The aggregation of individual random AR(1) models generally leads to an AR(∞) process. We provide two consistent estimators of aggregate dynamics based on either a parametric regression or a minimum distance approach for use when only macro data are available. Notably, both estimators allow us...

This letter evaluates forecasts from probit models that use the slope of the yield curve to forecast recessions. These models give reliable non-probabilistic warnings of recessions, but the estimated probabilities do not match the conditional frequency of recession months.

Using an empirical likelihood approach, we show that generalized linear models can still be consistently estimated even if dependent variables are not missing at random, and derive a Hausman test by comparing this estimator to the standard one.

We introduce non-linear fiscal reaction functions with endogenously estimated state-varying thresholds to capture the behaviour of fiscal policy authorities during “good” and “bad” times. These thresholds vary with the level of debt, the economic cycle and a financial pressure index.

I use a spatial Durbin model to estimate the effects of taxes on state economic growth. Results indicate that taxes have negative short-run and long-run own-state and spatial spillover effects on state growth.