Quantitative Easing Program Research Articles

Multiple Structural Breaks in Interactive Effects Panel Data Models

ABSTRACTThis paper develops new econometric methods for multiple structural break detection in panel data models with interactive fixed effects. The new methods include tests for the presence of structural breaks, estimators for the number of breaks and their location, and a method for constructing asymptotically valid break date confidence intervals. The new methodology is applied to a large panel of US banks for a period characterized by massive quantitative easing programs aimed at lessening the impact of the global financial crisis and the COVID‐19 pandemic. The question we ask is as follows: Have these programs been successful in spurring bank lending in the US economy? The short answer turns out to be: “No”.

Anatomy of wage rigidity in China: Lessons from the global financial crisis for post-pandemic recovery

This study examines the extent and cause of Chinese firms’ labour cost adjustment during the 2008 global financial crisis (GFC). First, we confirm that some typical features of downward nominal wage rigidity during the recession period coincide with the implementation of the Labour Contract Law, covering wages and social security payments. Second, we find that firms with higher shares of casual workers could lower their labour cost more effectively. The overall results demonstrate that the Quantitative Easing programme was necessary for counteracting the economic downturn during the GFC. Therefore, the length of this on-going crisis would be affected by wage rigidity in the economy. This study has implications for addressing the economic downturn in China following the COVID-19 pandemic, which is characterised by a high level of unemployment.

Conventional vs. unconventional monetary policy under credit regulation

Abstract We provide empirical evidence that the impact of quantitative easing (QE) programs on investment is weaker for countries with high-credit market regulations. We then extend a simple DSGE model with segmented financial markets to include credit regulation and examine its impact on the transmission of conventional and unconventional monetary policies. In our model, the government requires banks to hold a fraction of their assets in government debt. We show that the presence of such regulation can invert monetary transmission under QE policy: An expansionary QE program raises term premiums on corporate bonds and causes a contraction instead of an expansion in the economy. Such a perversion is absent under conventional policy. Further, in contrast to Carlstrom et al. (2017), we show that a simple Taylor rule welfare dominates a term premium peg under financial shocks, while the peg does better in the case of non-financial shocks.

Dynamic Spillovers from US (Un)Conventional Monetary Policy to African Equity Markets: A Time-Varying Parameter Frequency Connectedness and Wavelet Coherence Analysis

Since the implementation of unconventional monetary policies (UMPs) by the US in response to the global financial crisis (GFC) and the COVID-19 pandemic, there have been increasing concerns that these forward guidance and quantitative easing programmes have had spillover effects on global equity markets. We specifically question whether the implementation of these UMPs have had spillovers to African equities, which have been previously speculated to be decoupled from global markets and shocks. Time-varying-parameter (TVP) frequency connectedness and wavelet coherency methods were used to examine the dynamic time-frequency spillovers between daily time series of the US shadow short rate and African equities returns/volatility between 1 January 2007 and 31 March 2023. On one hand, the TVP frequency connectedness analysis reveals robust long-run spillovers from US monetary policy to African equity markets during specific periods: 2009, 2013, 2020, and 2021. These coincide with instances when the Federal Reserve announced their transition from conventional to unconventional monetary practices and vice versa. On the other hand, the wavelet analysis provides insights into the ‘sign’ of the spillovers, indicating mixed phase dynamics during UMPs responding to the GFC. In contrast, anti-phase or negative co-movements characterize UMPs implemented during the COVID-19 pandemic, implying that these policies increased both returns and volatilities to African equities. Altogether, we conclude that US UMP has increasing deteriorated market efficiency and amplified portfolio risk in African equities whilst during ‘normalization’ periods US monetary policy has little transmission effect.

The Impact of Quantitative Easing on Stock Prices in the U.S. Stock Market - Structural VAR Model Analysis

In an effort for future investment implications, the current study examined the relationship between historical Quantitative Easing (QE) programs and the stock market. This study analyzed weekly basis data in the United States between 2007 and 2023. Through a Vector auto-regression (VAR) model, a significant rise following a quick drop in stock prices to a positive shock in QE was discovered, indicating lagged response. Further robustness check proved the validation of relationship, by sectioning the whole data set into 4 periods corresponding to four QE programs, except relatively insignificant effects in QE2 and QE3 periods. These lagged responses were pointed out firstly in this paper and connected with policy motivations and contemporaneous economy environment across programs. The findings may enable investors to anticipate market movements and generate respectable returns in the event of such unconventional money shocks.

Examining spillovers and connectedness among commodities, inflation, and uncertainty: A quantile-VAR framework

This paper explores dynamic interactions and connectedness between inflation, commodities, and economic and monetary policy uncertainty during various market phases between 1985 and 2022, developing upon the innovative quantile-VAR methodology. Results reveal that inflation exhibits strong interlinkages with money supply, as would be expected, along with the price of gold during periods of low-price levels, while presenting a strong positive relationship with both oil valuations and the money supply during periods representative of moderate or average pricing behaviour. Moreover, inflation is identified to be a receiver of direct influence and broad connectedness, especially during the Global Financial Crisis and during episodes of US-based quantitative easing programmes, while exhibiting even more pronounced effects during the COVID-19 pandemic. Money supply is identified to be the most receptive to overall external influence from the selected variables. Furthermore, economic policy uncertainty is identified as the strongest source of influence, with effects surpassing that of monetary policy uncertainty. Market risk is identified to possess the strongest effects at the highest quantiles. This study provides insight into the interconnectedness of the real economy and financial markets across various economic conditions.

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.

A Study On Perception Of Millennials On Fintech And Cryptocurrency

A generation of millennials is rewriting the rules of the investment and Fintech industry. In contrast to the past when they played a relatively passive role, they now are leading some of the hottest trends in the industry. Today, it is the millennials who are driving many hot investment industries. For example, Robin hood a company founded by millennials, has disrupted the stock market and investment industry. The Federal Reserve's expansionary policies during the Covid-19 pandemic resulted in significant gains in cryptocurrencies and other assets. The Federal Bank responded to the trend of inflation and deflation by lowering interest rates and implementing a quantitative easing programme that pushed its balance sheet to over $8.5 trillion. This, in turn, led many millennials to seek alternative assets that offered better returns than cash. Cryptocurrencies have emerged as one of the most popular assets among millennials.

Quantitative Easing and Safe Asset Scarcity: Evidence from International Bond Safety Premia

Through large-scale asset purchases, widely known as quantitative easing (QE), central banks around the world have reduced the available supply of safe assets. We examine the effects of the European Central Bank’s asset purchases in the 2015-2021 period on an international panel of bond safety premia from four highly rated countries: Denmark, Germany, Sweden, and Switzerland. We find statistically significant negative effects for all four countries. This points to a novel and important international spillover channel of QE programs to bond safety premia that operates via changes in the perceived relative scarcity of safe assets across international bond markets.

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.

Research on the Corporate Bond Risk Factors

The global bond market is greater than the global equity market meanwhile it grows gradually in recent years. Issuing corporate bonds is an ideal channel for enterprises to raise funds in the course of COVID-19 and also provides resilience in the market. Moody's, Standard & Poor's and Fitch are well-known global credit rating agencies and suggest investors purchasing investment-grade bonds for reasonable risks and returns. But local credit rating agencies have limited capacities to appraise local bonds. In the COVID-19 crisis, widen yield spreads represent likelihood of default which can be a measure of credit risk. Besides, government interventions (i.e., Quantitative Easing Program) can effectively eliminate credit risks and Confucian culture is a factor in assessing credit risks of corporate bonds. As for liquidity risk, Chinese bond market is less liquid than the US bond market and financial bonds are the most liquid in the Chinese market. The liquidity risk is caused by inaccurate information and market risk tolerance whereas market risk tolerance integrates credit and liquidity, the main measurement of liquidity risk is transaction cost which means that higher transaction cost can impede liquidity in the bond market. Finally, market risk comprises of COVID-19 pandemic, market design and biodiversity risk. The epidemic tightens the financial condition of developing countries and depreciates the currency of the bond market which raises term structure of interest rate up. A well-designed financial market system can help stabilize fluctuations during financial crisis. Besides, biodiversity risk is relevant to the operation apartment of companies.

The European Central Bank and green finance: How would the green quantitative easing affect the investors' behavior during times of crisis?

In July 2021, the European central bank (ECB) announced the application of new environmental criteria to purchase private assets as part of its Quantitative Easing (QE) program. Using a Bayesian VAR model with time varying parameters and stochastic volatility (TVP-BVAR-SV), we investigate the transmission of Green bond shocks to the stock market during the pre-and-post COVID-19 pandemic. We document a nonlinear relation between the green bonds and the green equities. Our findings suggest that the ECB's Green QE can drive investors towards green investment in the stock market through the green bond market during the non-crisis period. However, we show that the proper transmission of Green QE shocks to the stock market depends on the economic conditions and could not be effective during the crisis period. Our results also support previous findings that state the growing demand for sustainable investing after COVID-19. These findings have important implications for investment professionals, policymakers, and environmentally concerned actors.

The 1932 Federal Reserve Open‐Market Purchases as a Precedent for Quantitative Easing

AbstractThe $1 billion open‐market operation conducted by the Federal Reserve, at the height of the Great Depression, was a successful precedent to the recent Quantitative Easing (QE) programs. The 1932 program entailed large purchases of medium‐ and long‐term securities over a 4‐month period. An event study analysis indicates that the program dramatically lowered medium‐ and long‐term Treasury yields. A segmented markets model is used to analyze the effects of the open‐market purchases on the economy. A significant degree of financial market segmentation is estimated, and partly explains the observed upturn in output growth. Had the Federal Reserve continued its operations and used the announcement strategy used in QE1, the Great Contraction could have been attenuated earlier. Our historical analysis suggests that the Federal Reserve in 2008 had a good predecessor to its actions.

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.

Quantitative easing in the United States in 2020 after the covid-19: effects on U.S. economy and implications from historical policy about how to improve the policy

The quantitative easing program, an unconventional monetary policy, was implemented in the U.S. for four rounds till 2020 to stimulate the economy during some recessionary times. This paper discussed the instrument and the objective of the four rounds of quantitative easing policy and the similarity of the aims. The paper focused on the impacts on the U.S. economy of the policy, both the positive and the negative. The policy led to economic growth, combating the recession and possibly induced inflation. They also lead to the depreciation of the U.S. dollar in different periods and increase income inequality and wealth inequality. Then this paper discusses the policies that can be used to deal with the problem that may happen during the fourth round of the quantitative easing program, which mainly focuses on supply-side policies.

Development of Modern Approaches to Exchange-Traded Financial Asset Evaluation

Estimation of exchange-traded financial asset fair value is one of the most important tasks in modern financial science. However, the importance of methods for prediction of future prices is constantly changing. The study provides a comparative analysis of fundamental and technical analysis methods, reveals their advantages and disadvantages. Such characteristics of fundamental analysis as profit, income, profitability and the level of debt burden are considered in detail, the degree of their influence on the price of securities is analyzed. After the study, conclusions were drawn about the increasingly narrow use of technical analysis during short-term and investment problem solution. A prediction is given for a further decrease of fundamental analysis importance as the main method of assessment. To obtain these conclusions, we used statistical data reflecting the dynamics of exchange-traded assets when companies entered IPOs. The data obtained indicate a clear correlation between the innovation component of a business, market share and its price. At the same time, the company profit has finally ceased to be the main characteristic of the business during its assessment. Additionally, they studied the relationship between the fairness of exchange-traded asset evaluation and quantitative easing (QE) programs. Conclusions are made about the need to increase the forecast prices in the case of a soft monetary policy application.

Are Banks Still a Risk Source for Stock Market? Some Empirical Evidences

The global financial crisis of 2008 proved that what initially appeared to be relatively small losses in the financial system can be magnified to systemic ones. The European Union debt crisis has thus revived interest in the interdependence across different markets, especially sovereign debt markets and the banking sector, and in the interlinkages among idiosyncratic and common shocks. This paper analyzes the evolution over time of the incidence of common shocks on the main Italian banking groups starting from the period of European Central Bank’s Quantitative Easing program. Results show that the banking sector is no longer perceived by the markets as a common risk source, overcoming the negative picture coming from the financial crisis of 2008–2009. The analysis also suggests that the common risk is broadly affected by the ECB monetary policy, and the idiosyncratic risk is linked to the recapitalization processes.

Structural Breaks in Interactive Effects Panels and the Stock Market Reaction to COVID-19

Dealing with structural breaks is an essential step in most empirical economic research. This is particularly true in panel data comprised of many cross-sectional units, which are all affected by major events. The COVID-19 pandemic has affected most sectors of the global economy; however, its impact on stock markets is still unclear. Most markets seem to have recovered while the pandemic is ongoing, suggesting that the relationship between stock returns and COVID-19 has been subject to structural break. It is therefore important to know if a structural break has occurred and, if it has, to infer the date of the break. Motivated by this last observation, the present article develops a new break detection toolbox that is applicable to different sized panels, easy to implement and robust to general forms of unobserved heterogeneity. The toolbox, which is the first of its kind, includes a structural change test, a break date estimator, and a break date confidence interval. Application to a panel covering 61 countries from January 3 to September 25, 2020, leads to the detection of a structural break that is dated to the first week of April. The effect of COVID-19 is negative before the break and zero thereafter, implying that while markets did react, the reaction was short-lived. A possible explanation is the quantitative easing programs announced by central banks all over the world in the second half of March.

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.

Bank loans during the 2008 quantitative easing

We examine the effect of quantitative easing on the supply of bank loans. During the Fed’s quantitative easing programs, lending banks reduced relatively more loan spreads, offered longer loan maturities, provided larger loans, and loosened more covenants for firms whose long-term bond ratings were below BBB and were lower than those with investment-grade bond ratings. Furthermore, we find that new bank loans in this period were associated with a reduction in a firm’s value and an increase in default risk. These results indicate that banks took greater risk during the 2008 quantitative easing by relaxing lending standards to relatively riskier borrowers.