The national total expenditure of a country is precipitated on several factors of which revenue generated could be one and very significant. This paper therefore examines the contribution of some selected sources of Nigerian government revenue to total national expenditure. Statistical and econometric techniques used for the data analysis are unit root test, cointegration test, combined estimators’ analysis, the error correction model (ECM) and the feasible generalized linear (FGLS) estimators. Results showed that the variables are non stationary but are stationary at first difference. The long-run relationship of total expenditure on oil revenue, non-oil revenue, federation account and federal retained revenue revealed that the variables are co-integrated and required the use of combined estimators. The effect of non-oil revenue and federal retained revenue is very significant. Investigations on the short-run modeling necessitated the use of FGLS estimators. The effect of ECM and federal retained revenue is very significant. Consequently, other sources of revenue apart from federal retained revenue need to be enhanced and tailored towards improving economic growth and development through national expenditure.
The global financial and European debt crises exposed the need for a new approach to fiscal modeling to support decision making analytically. With this purpose, in the following paper we present a macro-fiscal model. By capturing macro-fiscal interlinkages, especially those between fiscal variables and exchange rates, the model enables to analyze various fiscal scenarios with the focus of its impact on debt sustainability and real sector, as well as to conduct forecasting exercises, for small open economies with potentially large share of foreign currency denominated debt in the overall public debt. Finally, the model is applied to Georgian economy to interpret its’ historical data, provide an optimal policy path for future and analyze debt sustainability under several stress scenarios.
News might trigger jump arrivals in financial time series. The “bad” news and “good” news seem to have distinct impact. In the research, a double exponential jump distribution is applied to model downward and upward jumps. Bayesian double exponential jump-diffusion model is proposed. Theorems stated in the paper enable estimation of the model’s parameters, detection of jumps and analysis of jump frequency. The methodology, founded upon the idea of latent variables, is illustrated with simulated data.
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