Stock market illiquidity and future UK GDP growth have a statistically significant negative relationship, which is more pronounced during periods of highly illiquid markets and weak economic growth. Market liquidity–based models are the only ones that significantly outperform GDP growth forecasts in the Bank of England’s inflation report.
What’s Inside?
Quantitative easing (QE) has been shown to work through the macro/policy news channel, the signaling channel, and the portfolio rebalancing channel. The authors statistically explore the impact of a fourth channel, stock market liquidity, on economic growth in the United Kingdom during 1Q1989–2Q2012. They find an inverse relationship between the two. There are two economic rationales for this result. First, liquidity can act as a signaling mechanism of investors’ expectations. Second, it can affect the real economy through investment channels. The authors also show that stock market liquidity and broad money supply are linked and the relationship is asymmetrical in form.
How Is This Research Useful to Practitioners?
The authors demonstrate that liquidity and future economic growth are inversely related after they account for other financial variables, such as the term spread, asset prices, and volatility. Thus, market liquidity can act as a leading indicator of economic growth. Moreover, the relationship strengthens during periods of high illiquidity and/or a weak economy.
The authors link stock market liquidity to macro liquidity provisions and thereby introduce an asymmetry into the relationship. They build a case for QE by statistically finding that if market liquidity had not decreased so dramatically since 2007, the depth of the UK recession would have been less severe by 2.3 percentage points.
From a methodological perspective, unlike some previous researchers, the authors conceptualize an asymmetrical relationship between liquidity and economic growth. This asymmetrical model suggests a regime switch that depends on illiquid/liquid market conditions and the state of the business cycle. The out-of-sample analysis also supports this regime-switching model.
Through formal statistical testing, the authors show that this model is the only one out of a wide range of models used in which forecasting accuracy outperforms the Bank of England’s inflation report. The study uses data generally available to policymakers, which makes the proposed model applicable in real life.
The authors find that the term structure and divisia money (a form of aggregation that weights the components of money according to their usefulness in transactions) also have statistical significance higher than that of global GDP growth and M4. As an aside, the authors find that the relationship of oil prices and stock market volatility with UK GDP growth has not been statistically significant.
How Did the Authors Conduct This Research?
The authors begin with a linear relationship in UK GDP growth and stock market illiquidity (liquidity) and a vector of control variables, such as lagged GDP growth, term spread, global GDP growth, and growth in real money. Because of the asymmetrical relationship between market liquidity and money supply, they use a nonlinear version of the relationship and introduce transition variables. The authors conduct statistical tests on both the linear and nonlinear relationships over moving windows of time while using different combinations of money supply, illiquidity, and control variables.
Stock market illiquidity is captured through the return-to-volume ratio (average of absolute daily return over daily volumes in monetary terms), and liquidity is captured through the return-to-turnover ratio. These measures are expressed in percentage deviations from their two-year moving average. The authors use FTSE 100 Index data for 1Q1989–2Q2012.
The authors approximate the term spread by using the yield spread between 10-year UK government bonds and the three-month T-bill rate. Annual real money growth is approximated by the growth in broad money (M4) and divisia money. US real GDP growth is used as a proxy for global economic activity.
Stock market data are sourced from Thomson Reuters Datastream, money supply from UK GDP growth is from the Bank of England, inflation information is from the Office for National Statistics database, and US GDP information is from the Federal Reserve Bank of Philadelphia.
Abstractor’s Viewpoint
The finding of links between an easily measurable factor, such as stock market liquidity, and GDP growth has important implications for policymakers, economists, and investors. As the authors suggest, it would also be helpful to extend this analysis to other key macrovariables, such as inflation.
Although the study supports the case for macro liquidity infusions to revive economic growth, it would also be insightful to evaluate the comparative efficacy of government spending programs to build long-term economic assets, such as infrastructure and new technology development. In addition, the evaluation of possible measures to prevent the formation of asset price bubbles and situations in which increased liquidity gets trapped would also be interesting.