Project topics and materials
Get Complete Project Material File(s) Now! »
INTRODUCTION
In many ways, macroeconometric modelling has provided crucial support to decisionmaking units at both national and international level. The prediction ability of reliable macroeconomic models has helped to improve the performance of world economies over the years. The building of advanced structural dynamic equation models tested on past data for forecasting experiments has improved the reliability of macroeconomic modelling. More policy makers are making use of such models while most donors rely on the output of these models when it comes to making decisions on fund allocation. In addition, credit allocated to progressive macroeconomic modelling has largely been enhanced by the introduction of social ingredients such as health and education.
The understanding of the macroeconomic returns on human capital has stimulated larger interest from both academics and donors. On many occasions, the two groups have been called to work on common grounds to bring helpful solutions to the issue.
However, several aspects of the dilemma remain unattended. Regions of the world that portray the poorest macroeconomic progress are the most vulnerable to human calamities. This constitutes a heavier burden placed on national budgets. The Southto- North dependency relationship remains pertinent as far as education and/or health is concerned. The inadequate health and education systems found in the poor regions of the world (mainly Sub-Saharan Africa) have largely contributed to the widening of the technological gap among developed countries and many of the less fortunate underdeveloped economies. This issue has been identified as part of the world’s developmental priorities on several occasions (see Millennium Development Goals, 2000)1. Nevertheless, for several economies where lack of good governance has eroded the efficiency of donors’ actions, more drastic solutions are needed.
1 The Millennium Development Goals comprise of eight goals that were established by 189 UN (United Nations) member states during the Millennium Summit held in 2000. The aim is to achieve the goals by the year 2015.
On many occasions, budget restrictions have forced policy makers to prioritise funding requirements using the criteria of return on investment. Development opportunities (sectors or areas) that have been identified as more productive (higher and faster return) have received larger consideration than others.
CHAPTER 1: GENERAL INTRODUCTION
1. Introduction
2. Problem statement and objectives of the study
3. Significance of the study
23 4. Outline of the rest of the study
CHAPTER 2: SOCIAL INGREDIENTS AND CONDITIONALCONVERGENCE IN THE STUDY OF SECTORAL GROWTH
1. Introduction
2. Background
3. The theoretical model
4. The data
6. Conclusion
CHAPTER 3: SOME POLICY EXPERIMENTS USING A MARSHALLIAN MACROECONOMETRIC MODEL: THE CASE OF SOUTH AFRICA
1. Introduction
2. Background
3. Overview of industrial sectors in South Africa
4. The use of disaggregation
5. Model specification
6. Estimations techniques
7. Loss functions for estimating the MMM-DA
8. Improving predictions using shrinkage techniques
9. Imposing restrictions
10. Data
11. Results discussion
12. Conclusion, study limitations and future research
