Is the consumption-income ratio stationary? Evidence from linear and nonlinear panel unit root tests for OECD and non-OECD countries

This paper applies recently developed heterogeneous nonlinear and linear panel unit root tests that account for cross-sectional dependence to 24 OECD and 33 non-OECD countries’ consumption-income ratios over the period 1951–2003. We apply a recently developed methodology that facilitates the use of panel tests to identify which individual cross-sectional units are stationary and which are nonstationary. This extends evidence provided in the recent literature to consider both linear and nonlinear adjustment in panel unit root tests, to address the issue of cross-sectional dependence, and to substantially expand both time-series and cross sectional dimensions of the data analysed. We find that the majority (65%) of the series are nonstationary with slightly fewer OECD countries’ (61%) series exhibiting a unit root than non-OECD countries (68%).

A Bootstrap Neural Network Based Heterogeneous Panel Unit Root Test: Application to Exchange Rates

This paper proposes a bootstrap artificial neural network based panel unit root test in a dynamic heterogeneous panel context. An application to a panel of bilateral real exchange rate series with the US Dollar from the 20 major OECD countries is provided to investigate the Purchase Power Parity (PPP). The combination of neural network and bootstrapping significantly changes the findings of the economic study in favour of PPP.

A Nonlinear Panel Unit Root Test under Cross Section Dependence

We propose a nonlinear heterogeneous panel unit root test for testing the null hypothesis of unit-roots processes against the alternative that allows a proportion of units to be generated by globally stationary ESTAR processes and a remaining non-zero proportion to be generated by unit root processes. The proposed test is simple to implement and accommodates cross sectional dependence. We show that the distribution of the test statistic is free of nuisance parameters as (N, T) −! 1. Monte Carlo simulation shows that our test holds correct size and under the hypothesis that data are generated by globally stationary ESTAR processes has a better power than the recent test proposed in Pesaran [2007]. Various applications are provided.

Two Studies on the Interplay between Social Preferences and Individual Biological Features

Biological features and social preferences have been studied separately as factors influencing human strategic behaviour. We run two studies in order to explore the interplay between these two sets of factors. In the first study, we investigate to what extent social preferences may have some biological underpinnings. We use simple one-shot distribution experiments to attribute subjects one out of four types of social preferences: Self-interested (SI), Competitive (C), Inequality averse (IA) and Efficiency-seeking (ES). We then investigate whether these four groups display differences in their levels of facial Fluctuating Asymmetry (FA) and in proxies for exposure to testosterone during phoetal development and puberty. We observe that development-related biological features and social preferences are relatively independent. In the second study, we compare the relative weight of these two set of factors by studying how they affect subjects’ behaviour in the Ultimatum Game (UG). We find differences in offers made and rejection rates across the four social preference groups. The effect of social preferences is stronger than the effect of biological features even though the latter is significant. We also report a novel link between facial masculinity (a proxy for exposure to testosterone during puberty) and rejection rates in the UG. Our results suggest that biological features influence behaviour both directly and through their relation with the type of social preferences that individuals hold.