Missing data or missing values are a common phenomenon in applied panel research and of great interest for unit root testing. The standard approach the literature is to balance by removing units and/or trimming time period all units. However, this can be costly terms lost information. Instead, existing tests could extended case unbalanced panels, but often difficult because observations affect ...

This study examines the impact of Foreign Direct Investment (FDI) on agricultural sector in Ivory Coast from 1990 to 2018. Phillips-Peron tests and augmented Dickey-Fuller were employed for a unit root variables. The Johansen Cointegration test VAR used estimate stability normality. VECM analyze short-term long-term dynamics. Results reveal that FDI has negative long run relationship but signif...

objectives: gingival recession can lead to root exposure and discomfort for patients. there are various techniques for root coverage. the aim of this study was to compare the use of gingival unit graft (palatal graft including the marginal gingiva and papillae) with free gingival graft for treatment of localized gingival recession. materials and methods: in this randomized controlled clinical t...

Recently, Diebold and Kilian [Unit root tests are useful for selecting forecasting models, Journal of Business and Economic Statistics 18, 265-273, 2007] and Niwitpong [Effect of Preliminary unit roots on predictors for an unknown mean AR(1) process, Thailand Statistician 7, 71-79, 2009] indicated that the preciseness of a predictor for an AR(1) process can be increased by using the preliminary...

Using local-to-unity detrending, a modified momentum-threshold autoregressive test is derived to allow the unit root hypothesis to be tested against an alternative of asymmetric stationarity about a deterministic trend. Monte Carlo evidence is presented to show the increased power of the proposed test in the presence of asymmetric adjustment relative to the familiar Dickey-Fuller (1979) test an...

In this paper a Bayesian approach to unit root testing for panel data models is proposed based on the comparison of stationary autoregressive models with and without individual deterministic trends, with their counterpart models with a unit autoregressive root. This is done under cross-sectional dependence among the units of the panel. Simulation experiments are conducted with the aim to assess...