Federal Funds Rate Research Articles

Liquidity Preference, Interest Rate Spread, and the Transformation of the US Financial System

This article examines empirical patterns of interest rate spreads between yields on long-term corporate bonds and the Federal Funds Rate (FFR) in the United States over the period from 1960 through 2023. Since the early 1980s, discernible patterns of interest spreads have emerged, revealing marked deviations in corporate bond yields from the FFR. We focus on financial market forces particularly arising from financial intermediaries in analyzing these patterns. To this end, the article develops a theoretical framework based on the concept of liquidity preference in Keynes’s 1937 papers and the works of Hyman Minsky and Victoria Chick. We also conduct cointegration analyses for corporate bond yields, the FFR, and financial intermediaries’ leverage ratios. Overall, our empirical results indicate that the relationship between the FFR and corporate bond yields—particularly with respect to their long-run relationship and interest rate markups—has markedly changed since the 1980s and is significantly affected by financial intermediaries’ asset/capital leverage ratios. As a policy implication, regulatory reforms aimed at enhancing the Federal Reserve Bank’s capacity to steer long-term rates and contain intermediaries’ balance sheet leverage, particularly those centered on risky asset trading to increase gains from price differentials, are required JEL Classification: B26, E11, E43, E52

Sectorial economic activity and Divisia monetary aggregates

Abstract This paper assesses the information content and predictive capabilities of Divisia monetary indicators concerning sector-specific economic activities. Although existing evidence strongly supports the informative nature and predictive potential of various Divisia indicators at an aggregate level, studies focusing on Divisia information content for specific industries are notably sparse. Sector-level data provide a more detailed insight into economic and labor market dynamics. By analyzing comprehensive sector-specific data on real GDP, value added, employment, and unemployment rates across thirteen diverse sectors in the United States, this paper investigates the predictive abilities of narrow and broad Divisia money across three categories (original, credit card-augmented, and credit card-augmented inside money). The results show that narrow Divisia money serve as robust predictors of sector-specific economic and labor market indicators, often surpassing the predictive capacity of the conventional Fed funds rate and slightly outperforming broad Divisia measures in relation to these indicators.

Dynamic spillovers between oil market, monetary policy, and exchange rate dynamics in the US

This study examines the dynamic network connectedness among the oil market, monetary policy, and exchange rate dynamics in the US. Two dimensions of the relevant markets—specifically, oil prices, interest rates, and US dollar value—along with their associated uncertainties, are analyzed. Our results suggest that the strongest source of risk transmission is oil market uncertainty, with exchange rate market uncertainty and the US dollar following behind. Monetary policy uncertainty emerges as the primary recipient of risk, followed by oil prices and federal funds rate. The results also show that cross-market spillovers are more prominent than within-market spillovers.

Nonseparability of credit card services within Divisia monetary aggregates

Abstract We use the New Keynesian Dynamic Stochastic General Equilibrium (DSGE) framework and Vector Autoregressive (VAR) to investigate the usefulness and relevancy of monetary services, augmented to include credit card transaction services. We use the new credit-card-augmented Divisia monetary aggregates in the models to further the existing research on their usefulness and relevancy. In this research, we compare three different monetary aggregates within the New Keynesian framework: (1) the aggregation-theoretic “true” monetary aggregate, (2) the credit-card-augmented Divisia monetary aggregate, and (3) the simple sum monetary aggregate. We acquire the following primary results. (1) The credit-card-augmented Divisia monetary aggregate tracks the theoretical (true) monetary aggregate, while simple sum does not. Although this result would be expected from the theory in classical economic models, the result is not an immediate implication of the theory in New Keynesian models and therefore needs empirical confirmation. (2) Under the recursive VAR framework, the credit-card-augmented Divisia monetary aggregate serves as a preferable monetary policy indicator compared to the traditional federal funds rate. (3) On theoretical grounds, we find that the separability condition for existence of a monetary aggregator function could fail, if credit card deferred payment services were excluded from the monetary services block, unless all markets are perfect.

Stock market responses to unconventional monetary policy shocks

We assess the impact of forward guidance and large-scale asset purchases (LSAPs) on stock market returns, finding that LSAP shocks during unconventional periods affect stock returns in a manner similar to federal funds rate (FFR) shocks during conventional periods.

Financial Conditions and Risks to the Economic Outlook

Financial conditions have swung considerably over the past two and half years. They moved from very accommodative levels in late 2021 to providing a significant drag on economic activity in 2022 and 2023. Since early this year, they eased moderately amid monetary policy communications signaling that the federal funds rate had likely reached its peak for this monetary policy tightening cycle.

A temporal information transfer network approach considering federal funds rate for an interpretable asset fluctuation prediction framework

This study explores the complex interdependencies among five major financial assets—S&P 500, Bitcoin, Crude Oil, Gold, and USD/EUR—from April 2015 to September 2022, emphasizing the importance of understanding global financial dynamics for robust financial management. We quantitatively analyze daily causal relationships using conditional transfer entropy, a method that surpasses traditional correlation analyses. By incorporating the effective federal funds rate into our models, we enhance predictive accuracy and account for monetary policy impacts, ensuring our findings are relevant to current economic conditions. Our results reveal significant causal networks, providing key insights into asset interdependencies that support advanced hedging strategies and effective diversification. This research improves prediction models through the innovative use of network-based features and offers practical strategies for managing multinational financial assets, with relevance across various economic scenarios.

US Dollar Exchange Rate Elasticity of Gold Returns at Different Federal Fund Rate Zones

We examine the relationship between gold prices and the U.S. dollar exchange rate, arguing that their interactions are state-dependent and asymmetric under different market conditions. State dependency hinges on different short-term interest rate zones. To prove this point, we determine three distinct levels or zones of the effective federal funds rate using SETAR(2,p) tests. Subsequently, we perform conditional least square estimations of log changes in gold prices as a function of log changes in the nominal broad U.S. dollar exchange rate index for each of the obtained zones. Their relationship is consistently inverse, suggesting that gold and the U.S. dollar are risk-hedging substitutes for normal market periods. This also implies that gold is a safe-haven asset against the U.S. dollar exchange rate risk against a broad range of currencies. The substitution is weaker in the low-interest rate zone, more robust in the intermediate zone, and very pronounced in the high zone. We also perform a Markov switching test on the double-log function of gold prices and the exchange rate. The tests show a pronounced inverse relationship, i.e., substitution between assets, at normal market conditions. The relationship becomes significantly positive during episodes of financial distress, indicating complementarity between gold and U.S. dollar assets.

Stock Return Prediction under US Federal Funds Rate Hike Based on Supervised Machine Learning

As US Federal Reverse Systems has continued to raise federal funds in the past few years in order to curb inflation, this has had a huge impact on chinese capital market. Investors and financial institude are actively engaged in predicting stock returns to maximize their investment income. This study constructs a model to analyze and predict the financial factor of stock income based on supervised machine learning methods and evaluate the results. The datasample is extracted from wind, for the period half a year before and after the recent federal funds rate hike. Utilizing machine learning packages in R, this paper construct models based on linear discriminant analysis, decision tree and random forest models. After constructing estimation models, this paper visualizes the prediction result by utilizing drawing package in R. It has been found that the random forest algorithm predicting model generates very successful results for the financial factor prediction as the model accuracy reaches 99%. According to the analysis, relevant model to predict financial factors and non-financial factors based on non-linear supervised machine learning algorithm can be built by investors or hedge fund agency to estimate stock performance in the future. This study also investigates the economic result of the Federal Funds Rate hikes, which is instructive for investors to make well-informed decisions.

Set-Identified Structural Vector Autoregressions and the Effects of a 100 Basis Point Monetary Policy Shock

Abstract I estimate impulse responses to a 100 basis point US monetary policy shock using setidentified structural vector autoregressions. Identified sets for these responses may be unbounded when the identifying restrictions admit zero impact response of the federal funds rate following a standard-deviation shock. Such a zero response is always admissible when there are fewer sign and zero restrictions than endogenous variables. This is the case under existing restrictions on the systematic component of monetary policy, which consequently yield uninformative identified sets. Additional sign and narrative restrictions yield informative identified sets and imply smaller output responses than some previous estimates.

Pengaruh FED Rate, Inflasi, dan Indeks Dow Jones terhadap IHSG di Indonesia Periode 2022-2023

<p><em>This study seeks to examine the impact and evolution of the following factors on the Composite Stock Price Index (IHSG): Fed Rate, Inflation in Indonesia, and the Dow Jones Index. Bank Indonesia, Investing.com, library databases, scholarly publications, and other secondary sources provided the data used in this study. In this study, the data was analyzed using the Ordinary Least Square (OLS) method of multiple linear regression. The data was processed using software and covers the research period from January 2022 to December 2023. The data was sourced from various sources, including the internet, scientific journals, and books. This study found that although the Federal Funds Rate variable does not affect the IHSG at all, inflation does, and the Dow Jones Index does affect the Dow Jones Index. At the same time, the IHSG is affected by all of the factors at the same time.</em></p>

Impacts of Shocks to U.S. Macroeconomic Variables on the Regional Economy of Georgia

This paper develops a way to analyze a regional economy and a large economy within a model. Using structural autoregression with block exogeneity and mutual independence assumptions as well as Cholesky factorization, we quantify the impacts of shocks to U.S. macroeconomic variables on the regional economy of Georgia. We found that the largest impact on Georgia's aggregate variables - consumer prices, real per capita personal income, and total employment - is the federal funds rate. For other shocks, Georgia's personal income is most affected by an increase in commodity prices, while Georgia's consumer prices are most affected by U.S. inflation. At the industry level, we found that the impact of real GDP is the largest and the impact of M2 is the smallest on output and employment in Georgia's industries, although the magnitude of the impact on employment is smaller and more short-lived than on output.

Conventional and unconventional shadow rates and the US state-level stock returns: Evidence from non-stationary heterogeneous panels

This study analyzes how monthly stock returns in the United States react to conventional and unconventional shadow rates from February 1994 to April 2023. The study uses a nonstationary heterogeneous panel data technique appropriate for analyzing large cross-sections and long periods. The analysis is separated into turbulent and tranquil periods. The findings suggest that, although the shadow rate is expected to align with the long-term rate, its ability to boost economic activity in the stock markets is only applicable in the short term. Despite the Federal Funds Rate (FFR) being unable to be lowered below zero bounds, the study shows results that support the effectiveness of the FFR in stimulating stock returns in the long run, particularly during crisis periods. The study also reveals that both conventional and unconventional shadow rates share a common feature, which is that they demonstrate how the stock markets can be downward-sticky in the long run with a rising shadow rate in virtually all 50 states in the U.S. The findings provide sturdy insights into the usefulness of unconventional monetary policy measures for stock market performance during crises and normal periods.

Can higher federal funds rates control mortgage lending during periods of high inflation and high house prices?

The U.S. is facing higher inflation since December 2020 along with higher house prices. After a sharp increase, house prices have started to decline very recently even more drastically – reminding us of the global financial crisis 2007–08. Rather late, from December 2021 onwards, the Fed started to increase the Fed funds rate. However, it is unclear whether the Fed funds rate can control bank lending activities – especially, mortgage lending. Surprisingly, our results suggest that the Fed funds rate fails to control mortgage lending during high inflation and high house prices in the absence of bank reserve requirements.

How to get monetary policy back on track

The presentation is based on research which focusses on the actions of the Federal Reserve and on other central banks around the world. The message of the presentation is that the Federal Reserve had got behind the curve—based on the widely quoted Taylor Rule. Now they have raised the federal funds rate, and they are much less behind the curve. The question now is how they and other central banks—including the European Central Bank and the Bank of Japan—will get back on track. That is the aim of the paper.

Indonesian Capital Market Response to U.S. Federal Funds Rate Increase Announcements

Indonesian Capital Market Response to U.S. Federal Funds Rate Increase Announcements

Perceptions About Monetary Policy

Abstract We estimate perceptions about the Federal Reserve’s monetary policy rule from panel data on professional forecasts of interest rates and macroeconomic conditions. The perceived dependence of the federal funds rate on economic conditions varies substantially over time, in particular over the monetary policy cycle. Forecasters update their perceptions about the Fed’s policy rule in response to monetary policy actions, measured by high-frequency interest rate surprises, suggesting that they have imperfect information about the rule. Monetary policy perceptions matter for monetary transmission, as they affect the sensitivity of interest rates to macroeconomic news, term premia in long-term bonds, and the response of the stock market to monetary policy surprises. A simple learning model with forecaster heterogeneity and incomplete information about the policy rule motivates and explains our empirical findings.

Do climate risks affect dirty–clean energy stock price dynamic correlations?

Prior studies have extensively exhibited an interest in exploring the connectedness between dirty and clean energy stock prices alongside the drivers of such price connectedness, shedding light on hedging strategies for finance practitioners. Nevertheless, no empirical research has examined whether climate risks, the emerging indicator for investors to handle the divestment of dirty energy stocks, have affected the time-varying dirty–clean energy equity price nexus. This study fills this gap by innovatively identifying dynamic conditional correlations (DCCs) between dirty and clean energy stock prices. An ARDL/NARDL model is applied to assess whether the climate risks affect such correlations by controlling for business cycles, funding liquidity, USD values, and oil market sentiments. Overall, we detect an undeniable negative impact of climate risks on the positive dirty–clean energy price dynamic correlations. Additionally, the NARDL model results reveal that a rise in federal fund rates exerts higher effects on the dirty–clean energy stock price comovements. Our findings suggest the strengthened potential of hedging clean energy stocks against dirty energy equities in case of escalating climate risks and heightened fossil fuel price volatilities. Furthermore, substantial attention is required to account for monetary policies' asymmetric effects on clean energy investment.

The effect of monetary policies on inflation: A fiscal perspective

We estimate how US monetary policies, namely the current fed funds rate, forward guidance, and large-scale asset purchases, affect inflation. The effect of large-scale asset purchases on inflation is found to be much smaller in the intended direction than the other policies. This difference is accounted for by the responses of fiscal policy. While fiscal policy is eased in response to monetary tightening in the short run, the long-run fiscal consolidation is less intense under unconventional monetary policies.

Monetary policy independence in an era of financial globalization: what theory suggests and the data in Oceania say

ABSTRACT This paper shows that under a floating exchange rate and integrated financial markets an optimizing central bank concerned about price and output stability partly accommodates a change in monetary policy abroad. A positive co-movement between the domestic policy rate and the foreign interest rate does not indicate lack of monetary policy independence but is an outcome of optimal policymaking in an open economy deeply embedded in the global financial architecture. Empirical evidence on overnight interest rate changes in Oceania (New Zealand, Australia) and US federal funds rate changes is consistent with this view.