The dynamics of bond market development, stock market development and economic growth
Bibliographic record
Abstract
Purpose The paper investigates whether Granger causal relationships exist between bond market development, stock market development, economic growth and two other macroeconomic variables, namely, inflation rate and real interest rate. The study aims to expand the domain of economic growth by including a more in-depth analysis of the possible impact that bond market and stock market development has on economic growth than is normally found in the literature. Design/methodology/approach This paper uses a panel data set of the G-20 countries for the period 1991-2016. It uses a panel vector auto-regression model to reveal the nature of any Granger causality among the five variables. Findings The paper provides empirical insights that both bond market development and stock market development are cointegrated with economic growth, inflation rate and real interest rate. The most robust result from the panel Granger causality test is that bond market development, stock market development, inflation rate and real interest rate are demonstrable drivers of economic growth in the long run. Research limitations/implications Because of the chosen research approach, the research results may lack theoretical foundations. Therefore, perhaps the more fully grounded interactive findings of this study can inspire theorists to fill the missing gap. Practical implications This paper includes lessons for policymakers in the G-20 countries seeking to stimulate economic growth in the long run and how they need to ensure greater stability of the interest rate and inflation rate as well as fully developing their financial markets, as both bond markets and stock markets are obvious drivers of economic growth. Originality/value This paper fulfills an identified need to study causal relationships between bond market development, stock market development, economic growth and two other macroeconomic variables, i.e. inflation rate and real interest rate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".