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This paper aims to develops an estimable hybrid model that combines the micro‐founded DSGE model with the flexibility of the atheoretical VAR model.

The model is estimated via the maximum likelihood technique based on quarterly data on real gross national product (GNP), consumption, investment and hours worked, for the South African economy, over the period of 1970:1 to 2000:4. Based on a recursive estimation using the Kalman filter algorithm, the out‐of‐sample forecasts from the hybrid model are then compared with the forecasts generated from the Classical and Bayesian variants of the VAR for the period 2001:1‐2005:4.

The results indicate that, in general, the estimated hybrid‐DSGE model outperforms the classical VAR, but not the Bayesian VARs in terms of out‐of‐sample forecasting performances.

The model lacks nominal shocks and needs to be extended into a small open economy framework.

The paper was able to show that, even though the DSGE model is outperformed by the BVAR, a microfounded theoretical DSGE model has a future in forecasting the South African economy.

To the best of the authors' knowledge, this is the first attempt to use an estimable DSGE model to forecast the South African economy.

The purpose of this paper is to review identified key features of teacher support and its influence on students’ career decision making and development. It also examines the types of research approaches to data collection and analysis in order to provide a more in-depth evaluation of this field of study.

The review examined 18 studies, the majority being quantitative in design. Cross-sectional and longitudinal effects of teacher support were investigated, and differences in teacher support relative to grade level and gender were considered.

Results indicated that since 2000, there has been an increase in the number of empirical studies of teacher support in the career development field, the majority involving middle and high school students. The most commonly cited frameworks that underpin the studies are the social cognitive career theory, the career construction theory and Super’s career development theory. The most frequently used instrument for data collection was the teacher support scale (Metheny et al., 2008).

The review will be beneficial to researchers, teachers and policy makers seeking to optimize support systems for students’ career development. The findings contribute to further theory development and have practical implications for the career guidance field. Recommendations for future research and practice are suggested.