Effects Of Quantitative Easing Research Articles

Analysis of the Impact of Quantitative Easing Monetary Policy on the Japanese Economy

Quantitative easing (QE), which was implemented as a measure to address deflation and promote economic growth, is subject to varying interpretations regarding its effectiveness to Japan economy. Supporters attribute the efficacy of quantitative easing (QE) to its role in mitigating a more severe economic decline through the stabilization of asset prices and the maintenance of low interest rates, so preventing future crises. Nevertheless, it is important to acknowledge that divergent viewpoints shed light on the challenges associated with attaining long-term economic expansion. These challenges are often attributed to persistent structural concerns such as a progressively aging population, restrained levels of consumer demand, and cautious levels of company investment. Critics express apprehensions regarding the inadvertent ramifications of extended quantitative easing (QE), encompassing imbalances within financial markets and potential threats to financial stability. This abstract presents a synthesis of several perspectives, highlighting the intricate relationship between quantitative easing (QE) policies and Japan's underlying economic issues. It contributes to a nuanced discussion on the overall effectiveness of QE in the Japanese context.

Quantitative Easing, Bond Risk Premia and the Exchange Rate in a Small Open Economy

We assess the impact of large-scale asset purchases, commonly known as quantitative easing (QE), conducted by Sveriges Riksbank and the European Central Bank (ECB) on bond risk premia in the Swedish government bond market. Using a novel arbitrage-free dynamic term structure model of nominal and real bond prices that accounts for bond-specific safety premia, we find that Sveriges Riksbank’s bond purchases raised inflation and short-rate expectations, lowered nominal and real term premia and inflation risk premia, and increased nominal bond safety premia, suggestive of signaling, portfolio rebalance, and safe asset scarcity effects. Furthermore, we document spillover effects of ECB’s QE programs on Swedish bond markets that are similar to the Swedish QE effects only after controlling for exchange rate fluctuations, highlighting the importance of exchange rate dynamics in the transmission of QE spillover effects.

Risk-averse corporate investment behavior and the effectiveness of quantitative easing

This paper analyzes how risk-averse investment behavior in a liquidity trap can render quantitative easing ineffective under certain circumstances. For risk-averse firms that could lever either a risky investment project or a riskless alternative, I show that the real interest rate responsiveness of a relative net investment return causes both the interest-rate sensitivity of investment and the slope of the aggregate demand (AD) curve to bifurcate. Except for the scenario of sufficiently low investment return and high real interest rates, investment is positively related to real interest rates and the AD curve is downward sloping; under the circumstances, quantitative easing backfires but laissez faire helps stimulate investment instead.

The effect of quantitative easing on US sector returns

In this study, we used event analysis to examine whether abnormal returns can be observed for US sector returns at the time when quantitative easing was announced. In our investigation, we sought to identify the sectors in which the amount of money introduced into the economy as a result of quantitative easing. In addition, since the programme is basically implemented by the central bank in order to stabilise the economy, an examination of its effect on the sectors may provide guidance on which segments have reacted negatively, thus possibly requiring additional central bank or public intervention. In our results, we found consistency for all four QE programme in some sectors In the examination of the S&P 500 sector indices, surprisingly no significant abnormal return was found in the financial sector, by contrast, for the healthcare sector, as well as discretionary and general consumer goods, the stocks included in the sector index reacted in the same way for all 4 announcements.

Fifty shades of QE: Robust evidence

Fabo et al. (2021) show that papers written by central bank researchers find quantitative easing (QE) to be more effective than papers written by academics. Weale and Wieladek (2022) show that a subset of these results lose statistical significance when OLS regressions are replaced by regressions that downweight outliers. We examine those outliers and find no reason to downweight them. Most of them represent estimates from influential central bank papers published in respectable academic journals. For example, among the five papers finding the largest peak effect of QE on output, all five are published in high-quality journals (Journal of Monetary Economics, Journal of Money, Credit and Banking, and Applied Economics Letters), and their average number of citations is well over 200. Moreover, we show that these papers have supported policy communication by the world's leading central banks and shaped the public perception of the effectiveness of QE. New evidence based on quantile regressions further supports the results in Fabo et al. (2021).

Quantitative easing effectiveness: Evidence from Euro private assets

AbstractProponents of quantitative easing (QE) unconventional policy have rather overstated some evidence that structural time series models do not predict long‐term asset prices and yields as well as naive random walk forecasts, implying that predictions of price reversals cannot be profitable and, therefore, that QE effects are not transitory. Indeed, in this work we present evidence that naive models do not outperform structural vector autoregressive and Markov switching models in out‐of‐sample forecasting of corporate bond yields purchased by the European Central Bank, when the information set includes base money growth. It turns out that structural time series models provide additional information regarding the likelihood of price reversals, thus motivating investors to offset the effects of QE interventions if they perceive unconventional monetary policy regimes as temporary.

The effects of quantitative easing on Bitcoin prices

This study aimed to examine the impact of the US quantitative easing policy on Bitcoin Prices in 2017–2023. A Time-Varying Parameter VAR (TVP-VAR) model was constructed for discussing the price influence mechanisms of quantitative easing on Bitcoins. The study's empirical results showed that the impacts of quantitative easing policies on Bitcoin prices can vary over time, a temporary positive impact on Bitcoin prices through different channels was also observed. Furthermore, it was found to impose a long-term positive impact via the liquidity channel.

How quantitative easing changes the nature of sovereign risk

We model the market stabilization function of quantitative easing (QE) programs as a put option written by the central bank to bond holders. This implicit put option protects bond holders against tail risks, in particular sovereign credit risk. The contingent claims model (CCM) that we use to value the implicit put option has not been applied to QE in the literature before. Based on this model, we examine the effect of the European Central Bank’s bond purchases by QE on the sovereign credit risk of eight countries of the Economic and Monetary Union (EMU). Model simulations show that in times of market stress investors attached a high value to the implicit put option on sovereign bonds. This indicates that QE lowers investors’ perception of sovereign default risk. Understanding this effect of QE is important for addressing tail risks in the euro area via a backstop facility.

A Structural Time Series Analysis of the Effect of Quantitative Easing on Stock Prices

In this paper, a structural time series model is estimated to analyse the effect of quantitative easing (QE) on stock prices for the US, UK and Japan. The model is estimated by maximum likelihood in a time-varying parametric framework, using the DJIA, S&P500, NASDAQ, FTSE100 and the NIKKEI225 as the dependent variable and the balance sheet of the respective Central Bank as an explanatory variable, along with the unobserved components that account for the behaviour of other explanatory variables that are not explicitly specified in the model. The results show that QE had a significant but not exclusive effect on the DJIA, S&P500 and the NASDAQ, suggesting that these stock prices are also affected by other missing variables and cyclical movements. However, for the UK and Japan, no effect of QE on the FTSE100 and the NIKKEI225 is found, suggesting that variables other than QE are important for the rise in these stock prices. One plausible explanation for this result is that perhaps QE becomes effective only after a certain threshold level is met.

Are quantitative easing effects transitory? Evidence from out-of-sample forecasts

Purpose Advocates of quantitative easing (QE) policies have emphasized some evidence that structural models do not predict long-term asset yields as well as naive forecasts, implying that predictions of price reversals cannot be profitable and that QE effects are not transitory. The purpose of this study is to reconsider the out-of-sample forecasting performance of structural time series processes relative to that of a random walk with or without drift. Design/methodology/approach This study uses bivariate vector autoregression and Markov switching representations to generate out-of-sample forecasts of ten-year sovereign bond yields, when the information set is augmented by including the growth rate of the monetary base, and the estimation relies on monthly data from countries that have pursued unconventional policies over the last decade. Findings The results show that naive forecasts are not better than those of structural time series models, based on root mean squared errors, while the Markov model provides additional information on price reversals, through probabilistic inferences regarding policy regime switches, which can induce agents to counteract QE interventions and reduce their effectiveness. Originality/value The novel features of this work are the use of a large information set including the instrument of unconventional monetary policy, the use of a structural model (Markov process) that can really inform about potential asset price reversals and the use of a large sample over which QE policies have been pursued.

Walls of capital: quantitative easing, spatial inequality, and the winners and losers of Canada’s pandemic-era housing market

AbstractThis paper analyzes the Bank of Canada’s (BoC) pandemic-era quantitative easing (QE) programs and their distributive implications, focusing on the Canadian housing market. First, we analyse the priorities and effects of QE: increasing liquidity and encouraging lending and borrowing. Next, we identify the sectors of the economy most influenced by QE, highlighting that investment in real estate soared in comparison to other sectors. Finally, we present a case study of real estate transactions in Toronto, finding that the increased investment in residential and multi-family housing worked to the detriment of marginalised populations. In spatializing macrofinance and identifying monetary policy’s role in geographies of housing, we call for increased attention to central banks and the distributional effects of monetary policy.

Conservatorship, quantitative easing, and mortgage spreads: a new multi-equation score-driven model of policy actions

Abstract In this paper, the effects of United States (US) policy actions on mortgage-backed security and mortgage loan spreads are measured, by using data before, during, and after the US subprime mortgage crisis. We study the effects of the following policy actions: (i) the placement of Fannie Mae and Freddie Mac into US Government conservatorship; (ii) the US Federal Reserve quantitative easing (QE) programs. We provide the following contributions to the literature: (i) for a robust measurement of policy effects, a new multi-equation score-driven t-QVARMA (quasi-vector autoregressive moving average) model is used. (ii) In addition to the measurement of the effects of QE, the effects of government conservatorship are also measured in this paper. (iii) Furthermore, the data period of the relevant literature is extended to the period of June 1998 to March 2020.

Too Big to Fail? Effects of Quantitative Easing on Large Firms

Too Big to Fail? Effects of Quantitative Easing on Large Firms

An evaluation of quantitative easing effectiveness based on out-of-sample forecasts

<abstract> <p>A line of defense of quantitative easing (QE) policies has been developed around empirical evidence that time series models do not predict long-term asset prices and yields as well as naive random walk forecasts, implying that predictions of price reversals cannot be profitable and, therefore, that QE effects are not reversed. However, in this work we present evidence that for the Eurozone, Sweden, and the UK, which have pursued QE interventions, a random walk does not beat a Markov switching regimes model in out-of-sample forecasting and, at the same time, the switching process provides additional information regarding the likelihood of price reversals, thus inducing market participants to offset the effects of QE interventions whenever they perceive unconventional monetary policy regimes as temporary.</p> </abstract>

Quantitative easing with heterogeneous agents

We study the effects of Quantitative Easing (QE) in a heterogeneous-agents model with liquid and partially liquid wealth, and nominal rigidities. The direct macroeconomic effect of QE is determined by the difference in marginal propensities to consume out of the two types of wealth, which is large according to empirical studies. Therefore, the effects of QE on aggregate output and inflation are significant, according to the model. Indeed, the estimated model reveals that QE interventions greatly dampened the U.S. Great Recession, by expanding household liquidity. However, QE may have strong and adverse distributional effects, compared to interest rate policy.

Quantitative easing and economic growth in Japan: A meta‐analysis

AbstractWe present an original meta‐probit analysis for the effect of the Bank of Japan monetary policy on economic growth for the period 2001–2020, using 45 studies. We use impulse response functions in VAR type models to assess if the effects on output of unconventional monetary policies are significant (positive or negative) or not. Funnel asymmetry and precision effect tests do not provide a striking evidence of publication bias. Additionally, we do not find a consensus regarding the output growth effects during the quantitative easing years. Besides variables linked with the studies’ methodological features, other variables such as industrial production and the price level have a greater effect on the probability of reporting statistically significant (positive) effects of quantitative easing on output growth. However, one of the most important (policy) implications of our study is that the evidence for a significant real effect of unconventional monetary policy is weak.

Quantifying Stock and Flow Effects of QE

AbstractIn this paper, we focus on the transmission mechanism of quantitative‐easing (QE) policy and address which matters most: the size of the bond purchases in each period (flow effects) or the total amount of bonds taken away from the private sectors (stock effects). To this end, we estimate a dynamic stochastic general equilibrium (DSGE) model in which short‐ and long‐term bonds are imperfect substitutes due to market segmentation and preferred habitats, using Japan's data from the 1980s to 2017. We find that (i) Japan's data support imperfect substitutability between short‐ and long‐term bonds, which implies that government bond purchases by the Bank of Japan (BOJ) reduce the term premium, exerting an expansionary effect on economic activity and prices; (ii) government bond purchases by BOJ have compressed the 10‐year yields by 50–100 basis points as of the end of 2017; and (iii) the compression of the term premium has been mainly driven by stock effects, which underscores the importance of the size of BOJ's government bond holdings in determining the term premium.

Fifty shades of QE: Comparing findings of central bankers and academics

We compare the findings of central bank researchers and academic economists regarding the macroeconomic effects of quantitative easing (QE). We find that central bank papers find QE to be more effective than academic papers do. Central bank papers report larger effects of QE on output and inflation. They also report QE effects on output that are more significant, both statistically and economically, and they use more positive language in the abstract. Central bank researchers who report larger QE effects on output experience more favorable career outcomes. A survey of central banks reveals substantial involvement of bank management in research production.

Global financial crisis and COVID-19: Industrial reactions

We study industrial reactions to both the global financial crisis of 2008 and the COVID-19 pandemic. Although most industries in the U.S. suffered from the two events, the stock performance of most industries started to recover following the announcements of quantitative easing. Our results indicate that quantitative easing is effective in boosting investor confidence. We also find that the effect of quantitative easing in 2020 on stock performance is more significant for the industries that are more affected by the pandemic.

Fifty Shades of QE: Comparing Findings of Central Bankers and Academics

We compare the findings of central bank researchers and academic economists regarding the macroeconomic effects of quantitative easing (QE). We find that central bank papers find QE to be more effective than academic papers do. Central bank papers report larger effects of QE on output and inflation. They also report QE effects on output that are more significant, both statistically and economically, and they use more positive language in the abstract. Central bank researchers who report larger QE effects on output experience more favorable career outcomes. A survey of central banks reveals substantial involvement of bank management in research production. JEL Classification: A11, E52, E58, G28