We show that in sorting cross-sectional data, the endogeneity of a variable may be successfully detected by graphically examining the cumulative sum of the recursive residuals. An interesting case arises with a continuous or ordered (e.g., years of schooling) endogenous variable. Then, a...

We introduce a framework to test for exogeneity of a variable in a regression based on cross-sectional data. By sorting data with respect to a function (sorting score) of known exogeneous variables it is possible to utilize a battery of tools originally develped to detecting model...

The identification of average causal effects of a treatment in observational studies is typically based either on the unconfoundedness assumption or on the availability of an instrument. When available, instruments may also be used to test for the unconfoundedness assumption (exogeneity of the...

The identification of average causal effects of a treatment in observational studies is typically based either on the unconfoundedness assumption or on the availability of an instrument. When available, instruments may also be used to test for the unconfoundedness assumption (exogeneity of the...

In this paper, we use a non-parametric regression method to compare the transition process from high to low inflation with the implementation dates of central bank independence reforms. In a majority of the countries, price stability is achieved before more independence is given to the central...

Estimation in nonlinear time series models has mainly been performed by least squares or maximum likelihood (ML) methods. The paper suggests and studies the performance of generalized method of moments (GMM) and indirect estimators for the autoregressive asymmetric moving average model. Both...

In this paper a comparative study of the regime shift in inflation policies in New Zealand and Sweden is performed. We use a non-parametric regression method to decompose the inflation time series into three components of variation: a long-term trend, a medium-term (cyclical and transient...

In this paper we present guaranteed-content prediction intervals for time series data. These intervals are such that their content (or coverage) is guaranteed with a given high probability. They are thus more relevant for the observed time series at hand than classical prediction intervals,...