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This paper proposes a new test for structural instability in heterogeneous panels. The test builds on the seminal work of Andrews (2003) originally developed for time series. It is robust to non-normal, heteroskedastic and serially correlated errors, and allows for the number of post break observations to be small. Importantly, the test considers the alternative of a break affecting only some - and not all - individuals of the panel. Under mild assumptions the test statistic is shown to be asymptotically normal, thanks to the additional cross sectional dimension of panel data. This greatly facilitates the calculation of critical values. Monte Carlo experiments show that the test has good size and power under a wide range of circumstances. The test is then applied to investigate the effect of the Euro on trade. ; Ce papier propose un nouveau test pour détecter des changements structurels en fin d'échantillon dans des panels hétérogènes. Le test se construit sur le travail de Andrews (2003) conçu à l'origine pour des données temporelles. Le test est robuste à des erreurs non normales, hétéroscédastiques et autocorrélées. De plus, il permet au nombre d'observations suivant le changement structurel d'être petit. Le test considère l'hypothèse alternative que le changement structurel affecte seulement certains individus. Malgré des suppositions générales, la statistique du test est distribuée telle une normale. Cette propriété facilite grandement le calcul de valeurs critiques. Des résultats d'expériences de type Monte Carlo démontrent les excellentes propriétés du test. Pour finir, l'utilisation du test est illustré dans une évaluation de l'impact de l'Euro sur le commerce européen.

ABSTRACTThis paper investigates the performance of the tests proposed by Hadri and by Hadri and Larsson for testing for stationarity in heterogeneous panel data under model misspecification. The panel tests are based on the well known KPSS test (cf. Kwiatkowski et al.) which considers two models: stationarity around a deterministic level and stationarity around a deterministic trend. There is no study, as far as we know, on the statistical properties of the test when the wrong model is used. We also consider the case of the simultaneous presence of the two types of models in a panel. We employ two asymptotics: joint asymptotic, T, N →∞ simultaneously, and T fixed and N allowed to grow indefinitely. We use Monte Carlo experiments to investigate the effects of misspecification in sample sizes usually used in practice. The results indicate that the assumption that T is fixed rather than asymptotic leads to tests that have less size distortions, particularly for relatively small T with large N panels (micro‐panels) than the tests derived under the joint asymptotics. We also find that choosing a deterministic trend when a deterministic level is true does not significantly affect the properties of the test. But, choosing a deterministic level when a deterministic trend is true leads to extreme over‐rejections. Therefore, when unsure about which model has generated the data, it is suggested to use the model with a trend. We also propose a new statistic for testing for stationarity in mixed panel data where the mixture is known. The performance of this new test is very good for both cases of T asymptotic and T fixed. The statistic for T asymptotic is slightly undersized when T is very small (≤10).

In this study, the effect of real exchange rate on bilateral trade balance between Turkey and its 25 main trade partners is investigated for the period of 1996-2015 with heterogeneous panel data techniques. Trade balance model is estimated by using Mean Group (MG) estimator, which allows parameter heterogeneity, Common Correlated Effects Mean Group (CCEMG), and Augmented Mean Group (AMG) estimators, which both allow cross-section dependency and heterogeneity. Results indicate that the real exchange rate elasticity of the trade balance ranges between -0.40 and -0.45 and Marshall-Lerner (ML) condition is valid for Turkey. According to the results, the foreign income elasticity of trade balance ranges between 1.54 and 2.84, while for domestic income elasticity, it is found between -0.75 and -1.38. Country-specific results show that ML condition is valid for the USA, Belgium, Spain, Switzerland, Romania, and Russia at the bilateral level according to both CCEMG and AMG estimators.

Purpose
The purpose of this paper is to revisit the relationship between E-government and corruption using global panel data from 176 countries covering the period from 2003 to 2014, considering other potential determinants, such as economic prosperity (gross domestic product per capita [GDPPC]), price stability (inflation), good governance (political stability and government effectiveness) and press freedom (civil liberties and political rights) indicators. Hence, the main rationale of this study is to reexamine the conventional wisdom as to the relationship between E-government and corruption using panel data independent of any preexisting notions.


Design/methodology/approach
The probability reduction approach of empirical modeling proposed by Spanos (2009) is used to test the relationship. Secondary data were collected from the United Nations, the World Bank, Transparency International and Freedom House.


Findings
No statistical evidence was found for the idea that E-government has a positive impact on corruption reduction following a rigorous test of the proposition. However, strong evidence was found for the positive impact of a country's government effectiveness, political stability and economic status. There also appears to be some evidence for the effect of GDPPC and civil liberties. There is no evidence to prove that inflation and political rights have any corruption reducing the effect.


Research limitations/implications
Case studies suggest that E-government is helpful for curbing corruption. This study includes and examines some of the potential and important variables associated with corruption. Further research is encouraged and it should include more variables, such as national culture, poverty, religion and geography. Regarding methodology, a more parsimonious model must be sought to take into account adequately the entire probabilistic structure of the data.


Practical implications
The findings of the study demonstrate that E-government is less significant for reducing corruption compared to other factors. Hence, policymakers should further focus on other potential areas such as socio-economic factors, good governance, culture and transparency to combat corruption in addition to improving digital government.


Originality/value
This research applies a new methodological approach to the study of the relationship between E-government and corruption.