Allocation of public funds to R&;D: a portfolio choice-styled decision model and a biotechnology case study

A decision problem—allocating public research and development (R&D) funding—is faced by a planner who has ambiguous knowledge of welfare effects of the various research areas. We model this as a reverse portfolio choice problem faced by a Bayesian decision-maker. Two elements of the planner’s inferential system are developed: a conditional distribution of welfare ‘returns’ on an allocation, given stated preferences of citizens for the different areas, and a minimum risk criterion for re-allocating these funds, given the performance of a status quo level of funding. A case study of Canadian public research funds expended on various applications of agricultural biotechnology is provided. The decision-making methodology can accommodate a variety of collective expenditure and resource allocation problems.     

Testing for structural breaks in panel varying coefficient models: with an application to OECD health expenditure

In this article, we propose a model selection approach for testing structural breaks in a semiparametric panel varying coefficient model. Monte Carlo evidence shows that the proposed model selection approach performs well in finite sample settings. Applying the method to an empirical data, we find evidence of structural breaks in Organisation for Economic Co-operation and Development (OECD) health expenditure data by allowing for income elasticity to be state (income)-dependent. The relationship between health expenditure and income is subject to two types of structural changes: smooth changes over income and structural breaks in the time dimension. The findings hold for both foreign exchange rate-converted and Purchasing Power Parity-converted expenditure and GDP.     

Estimating the natural rates in a simple New Keynesian framework

The time-varying natural rate of interest and output and the implied medium-term inflation target for the US economy are estimated over the period 1983–2005. The estimation is conducted within the New Keynesian framework using Bayesian and Kalman-filter estimation techniques. With the model-consistent estimate of the output gap, we get a small weight on the backward-looking component of the New Keynesian Phillips curve—similar to what is obtained in studies which use labor share of income as a driver for inflation (e.g., Galí, Eur Econ Rev 45(7):1237–1270, 2001; Eur Econ Rev 47(4):759–760, 2003). The turning points of the business cycle are nevertheless broadly consistent with those of CBO/NBER. We find considerable variation in the natural rate of interest while the inflation target has been close to 2% over the last decade.     

Do dynamics and heterogeneity in panel data models matter?

This article investigates empirically the determinants of central banks’ reserve holdings for a large panel data set of developing and transition countries covering the period from 1975 to 2003. It estimates both a static and a dynamic relationship and applies estimators for homogeneous and heterogeneous panel data. Thereby, it examines the extent to which conclusions of panel data studies on the determinants of international reserve holdings are robust to the inclusion of dynamics as well as to the consideration of heterogeneity across countries. The results show that the neglect of dynamics and heterogeneity in country behaviour may lead to misleading inferences. Independently of the chosen estimation method, the findings suggest that trade openness and external debt are robust determinants of the level of reserves. Central banks take precautionary measures against the downside of the increasing international economic integration.