Key Macroeconomic Variables Research Articles

Monetary Policy and Interest Rate Spreads

This paper investigates the effects of monetary policy shocks and uncertainty about monetary policy on key macroeconomic variables and interest rate spreads — the term spread and credit spread. We use monthly data for the United States and a multivariate structural GARCH-in-Mean VAR model to estimate the effects on the growth rate of real output, the inflation rate, term spread, credit spread, and the policy rate. We find statistically significant effects on all economic and financial variables.

The Impact of Emerging Asia´s Demand on the Pacific Alliance Countries

ABSTRACT This article presents new evidence on the economic links between Asia and Latin America. Estimates from a Bayesian vector autoregression model show that key macroeconomic variables of the Pacific Alliance countries (Mexico, Peru, Chile, and Colombia) have a significant response to shocks on Emerging Asia’s demand. The spillover effects show that Peru is the country that is most vulnerable to income shocks in Emerging Asia. Nevertheless, developed economies’ shocks are still significant when it comes to explain the macroeconomic performances of Colombia, Chile, and especially, Mexico.

Loan to Value Ratio and Monetary Transmission Mechanism

Abstract Using a dynamic stochastic general equilibrium model (DSGE) with the housing sector, this paper evaluates the impact of housing collateral on the business cycle in the Czech economy. We devote special attention to the setting of the loan to value (LTV) ratio, which we believe plays an important role as a regulator of the monetary transmission mechanism. The impacts of LTV ratio are quantified by simulating the responses of alternative LTV level setting on key macroeconomic variables. Our simulations are based on an estimated DSGE model. Our approach allows us to understand better the responses of the real economy to the tightening of monetary policy moderated by different LTV levels. Our results show that higher loan to value ratios strengthen the effect of the monetary transmission mechanism to consumption and output.

Thoughts on a Fiscal Union in EMU

Abstract Using an estimated large-scale New Keynesian model, we assess the consequences of introducing a fiscal union within EMU. We differentiate between three different scenarios: public revenue equalisation, tax harmonisation and a centralised fiscal authority. Our results indicate that no country would significantly benefit from introducing any form of fiscal union. Comparing long-term, that is, steady state, effects we have winners and losers depending on the scenario. Differences in terms of business cycle statistics as well as in terms of risk sharing of asymmetric shocks are minor. This also explains why welfare differences are small across the fiscal union scenarios. A counterfactual exercise indicates that with a fiscal union regime already installed at the start of EMU, key macroeconomic variables would have reacted very similarly while debt dynamics would have changed notably.

Frequency-dependent real-time effects of uncertainty in the United States: evidence from daily data

ABSTRACT In this paper, we analyse the impact of uncertainty shocks at the daily-frequency on key macroeconomic variables for the United States. In doing so, we use a vector autoregressive (VAR) model, including the inflation rate, a real-time measure of economic activity and a measure of monetary policy as endogenous variables and decompose uncertainty effects into short, medium and long-term based on a discrete-time Fourier transformation. Aggregate results (prior to decomposition) show that an increase in economic uncertainty has a significant expansionary impact on monetary policy. However, when we decompose uncertainty into its short-, medium- and long-run components, we find that economic activity is affected negatively in a statistically significant manner to shocks in low-frequency uncertainty, while, statistically significant monetary expansion is observed under shocks to relatively high frequencies of uncertainty.

Environmental Policy Instrument Choice and International Trade

We develop a dynamic stochastic general equilibrium model to understand how environmental policy instrument choice affects trade. We extend the existing literature by employing an open economy model to evaluate three environmental policy instruments: cap-and-trade, pollution taxes, and an emissions intensity standard in the face of two types of exogenous shocks. We calibrate the model to Canadian data and simulate productivity and import price shocks. We evaluate the evolution of key macroeconomic variables, including the trade balance in response to the shocks under each policy instrument. Our findings for the evolution of output and emissions under a productivity shock are consistent with previous closed economy models. Our open economy framework allows us to find that a cap-and-trade policy dampens the international trade effects of the business cycle relative to an emissions tax or intensity standard. Under an import shock, pollution taxes and intensity targets are as effective as cap-and-trade policies in reducing variance in consumption and employment. The cap-and-trade policy limits the intensity of the import competition shock suggesting that particular policy instrument might serve as a barrier to trade.

The role of ECB communication in guiding markets

Economists and central bankers nowadays believe that forward guidance has become more important in a world in which key interest rates have hit their effective lower bounds (ELB). In the case of the European Central Bank (ECB), forward guidance should have increased the informational content of the introductory statements at the press conferences following ECB policy meetings. We examine whether such ECB communication adds information to a shadow interest rate that summarizes the overall policy stance as interpreted by financial markets. To measure communication, we use information based on ECB press releases distinguishing between topics like inflation, the real economy and monetary developments. We also look at the effect of communication on consensus expectations about key macroeconomic variables. The ECB’s assessment of the economy, i.e., communication related to economic growth, triggers movements in financial markets and thereby the shadow rate. Communication of the ECB through its press releases also causes professional forecasters to change their outlooks. Not only are their growth forecasts affected, but so are their expectations for M3 growth and inflation.

Large time‐varying parameter VARs: A nonparametric approach

SummaryIn this paper we introduce a nonparametric estimation method for a large Vector Autoregression (VAR) with time‐varying parameters. The estimators and their asymptotic distributions are available in closed form. This makes the method computationally efficient and capable of handling information sets as large as those typically handled by factor models and Factor Augmented VARs. When applied to the problem of forecasting key macroeconomic variables, the method outperforms constant parameter benchmarks and compares well with large (parametric) Bayesian VARs with time‐varying parameters. The tool can also be used for structural analysis. As an example, we study the time‐varying effects of oil price shocks on sectoral U.S. industrial output. According to our results, the increased role of global demand in shaping oil price fluctuations largely explains the diminished recessionary effects of global energy price increases.

Relationship between Foreign Macroeconomic Conditions and Asian-Pacific Public Real Estate Markets: The Relative Influence of the US and China

The aim of this paper was to examine the relationship between changes in the US and China macroeconomic conditions and the excess returns of nine Asian-Pacific public real estate markets (Singapore, Indonesia, Malaysia, the Philippines, Thailand, Australia, Taiwan, Hong Kong, and Japan). We found that there are insignificant correlations between macroeconomic conditions in the US and China and the real estate markets’ excess returns. Additionally, whilst the US macroeconomic factors show stronger causal relationships with the real estate markets in the long run, China’s macroeconomic variables have experienced a stronger causal relationship in the short run. Finally, key macroeconomic variables, such as the industrial production output index, long-term interest rates, and economic policy uncertainty, produced fluctuating impulse responses to shocks from the US and China. Overall, we conclude that the US economy continues to have a dominant influence in the Asian-Pacific real estate markets. However, during economic crises and in the short run, the impact of China’s economy grows significantly and outweighs that of the US In the context that a high degree of economic and financial integration has affected the interdependent level of international financial markets, the Asian-Pacific securitized real estate markets’ performances are also impacted by global shocks

Monetary Policy Shocks in the Russian Economy and Their Macroeconomic Effects

This section conducts an estimate of the impulse response function of key macroeconomic variables to monetary policy shocks in Russia. The estimates are carried out through a dynamic factor model (DFM) of the Russian economy with structural identification of shocks by imposing various sets of sign restrictions on the behavior of endogenous variables. We restricted first the monetary aggregate M2 only (a decrease in response to an increase of the Key rate), and then—simultaneously—M2, real effective exchange rate (an increase), and GDP (a decrease). We estimated the DFM using a large dataset of 58 macroeconomic and financial variables. The estimation results suggest that there is no decreasing response of consumer prices to an exogenous tightening of the interest rate policy of the Central Bank of Russia. This empirical evidence is supported implicitly by DFM-based predictions that under the imposition of such a decreasing response as an identifying restriction to the model, a positive interest rate shock is not transmitted through the interest rate channel of monetary policy to expected increases of the interest rates on commercial loans and private deposits. However, existing empirical evidence refutes this model-based result. Therefore, this study supports the view according to which a tightening of monetary policy in Russia is inefficient in terms of restraining inflation. In addition, monetary policy shocks negatively affect investments, retail sales, export and import, real wages, and employment. Different economic activities react differently to monetary policy shocks: export-oriented activities are not sensitive to these shocks, whereas domestic pro-cyclical activities (e.g. construction) can be substantially depressed in response to unexpected increases of interest rates. Finally, the expectations of economic agents are also significantly affected by shocks in the interest rate policy of the Bank of Russia.

Stock and bond returns correlation in Korea: Local versus global risk during crisis periods

This paper examines stock and bond returns correlation in Korea as an emerging market case study. The study covers the Asian financial crisis of 1997–1999 and the global financial crisis and European fiscal crisis of 2007–2012, plus non-crisis years that extend the sample period to 2005–2017. The sign of stock and bond returns correlation is shown to depend on the origin of risk triggering the crisis. In the local-risk driven crisis of 1997–1999, a flight to quality occurred across countries, causing stock and bond returns in Korea to decrease together. However, in the global-risk driven crises of 2007–2012, the flight to quality occurred across asset classes domestically, causing stock returns to decrease but bond returns to increase. Further, stock and bond returns correlation is found to relate systematically to changes in key macroeconomic variables, in particular, stock market volatility and a business leading indicator.

Forecasting Inflation in a Data-Rich Environment: The Benefits of Machine Learning Methods

Inflation forecasting is an important but difficult task. Here, we explore advances in machine learning (ML) methods and the availability of new datasets to forecast U.S. inflation. Despite the skepticism in the previous literature, we show that ML models with a large number of covariates are systematically more accurate than the benchmarks. The ML method that deserves more attention is the random forest model, which dominates all other models. Its good performance is due not only to its specific method of variable selection but also the potential nonlinearities between past key macroeconomic variables and inflation. Supplementary materials for this article are available online.

The nature of shadow bank leverage shocks on the macroeconomy

Recently a group of non-bank financial institutions, known as the shadow banks, has developed beside the traditional commercial banking sector in the US. Based on the argument of Serletis and Xu (2019) that the traditional banking was overtaken by shadow banks at around the year of 2000, I run two structural VAR models to examine the impact of shadow bank leverage shocks on some key economic indicators in pre-2000 and post-2000 periods. This is a new approach in the literature to examine how the macroeconomy is influenced by the shadow banking sector over time. I find that the traditional contractionary interest rate policy is not helpful to control the leverage of shadow banks. The impulse responses from the VAR models show that shadow bank leverage has become an important economic indicator during the post-2000 period because of its capacity to influence key macroeconomic variables. I suggest the policymakers controlling the leverage of the shadow banks besides the traditional contractionary monetary policy to prevent asset bubbles and maintain financial stability.

Structural break, US financial crisis and macroeconomic time series: evidence from BRICS economies

This paper analyses the overall trend of key macroeconomic variables of BRICS nations impacted by the US financial crises (2008–2009) through structural break analysis for period 2000–2013. Dummy variable model using exogenous break-date examines intercept and trend shift simultaneously in a single linear equation. The analysis statistically establishes that different variable of the countries endured varying level (severity) of the crisis impacted. Results found both immediate and lagged manifestation of the crisis impact on variables. The study’s exclusivity lies in exposing the exact period of crisis impact on each variable and also in capturing their exact trend movements. The paper contributes in isolating sensitive variables (sensitive/resilient to exogenous shocks) for further research on crises.

Monetary-fiscal policies interactions and optimal rules in Egypt

Purpose This paper aims to estimate a New Keynesian small open economy dynamic stochastic general equilibrium (DSGE) model for Egypt using Bayesian techniques and data for the period FY2004/2005:Q1-FY2015/2016:Q4 to assess monetary and fiscal policy interactions and their impact on economic stabilization. Outcomes of monetary and fiscal authority commitment to policy instruments, interest rate, government spending and taxes, are evaluated using Taylor-type and optimal simple rules. Design/methodology/approach The study extends the stylized micro-founded small open economy New Keynesian DSGE model, proposed by Lubik and Schorfheide (2007), by explicitly introducing fiscal policy behavior into the model (Fragetta and Kirsanova, 2010 and Çebi, 2011). The model is calibrated using quarterly data for Egypt on key macroeconomic variables during FY2004/2005:Q1-FY2015/2016:Q4; and Bayesian methods are used in estimation. Findings The results show that monetary and fiscal policy instruments in Egypt contribute to economic stability through their effects on inflation, output and debt stock. The monetary policy Taylor rule estimates reveal that the Central Bank of Egypt (CBE) attaches significant importance to anti-inflationary policy and (to a lesser extent) to output targeting but responds weakly to nominal exchange rate variations. CBE decisions are significantly influenced by interest rate smoothing. Egyptian fiscal policy has an important role in output and government debt stabilization. Additionally, the fiscal authority chooses pro-cyclical government spending and counter-cyclical tax policies for output stabilization. Again, past values of the fiscal instruments are influential in the evolution of the future fiscal policy-making process. Originality/value A few studies have examined the interaction between monetary and fiscal policy in Egypt within a unified framework. The presented paper integrates the monetary and fiscal policy analysis within a unified dynamic general equilibrium open economy rational expectations framework. Without such a framework, it would not be easy to jointly analyze monetary and fiscal transmission mechanisms for output, inflation and debt. Also, it would be neither possible to contrast the outcome of monetary and fiscal authorities commitment to a simple Taylor instrument rule vis-à-vis optimal policy outcomes nor to assess the behavior of monetary and fiscal agents in macroeconomic stability in context of an active/passive policy decisions framework.

Uncertainty, Financial Markets, and Monetary Policy over the Last Century

What has been the effect of uncertainty shocks in the U.S. economy over the last century? What are the roles of the financial channel and monetary policy channel in propagating uncertainty shocks? Our empirical strategies enable us to distinguish between the effects of uncertainty shocks on key macroeconomic and financial variables transmitted through each channel. A hundred years of data further allow us to answer these questions from a novel historical perspective. This paper finds robust evidence that financial conditions captured by both borrowing costs and the availability of credit have played a crucial role in propagating uncertainty shocks over the last century. However, heightened uncertainty does not necessarily amplify the adverse effect of financial shocks, suggesting an asymmetric interaction between uncertainty and financial shocks. Interestingly, the monetary policy stance seems to play only a minor role in propagating uncertainty shocks, which is in sharp contrast to the recent claim that binding zero-lower-bound amplifies the negative effect of uncertainty shocks. We argue that the contribution of constrained monetary policy to amplifying uncertainty shocks is largely masked by the joint concurrence of binding zero-lower-bound and tightened financial conditions.

Reconciling Output and Unemployment Fiscal Multipliers

ABSTRACTThis paper provides a macroeconomic model that can simultaneously explain output and unemployment multipliers which are consistent with empirical evidence. To this end, this paper has merged and investigated a model with deep habit formation in private and public consumptions and a model with a labour market friction that generates involuntary unemployment stemming from the monopolistic power of differentiated labour services. The model with a baseline calibration seems to produce quantitatively plausible responses of key macroeconomic variables in response to a government expenditure shock.

Forecasts in times of crises

Financial crises pose unique challenges for forecast accuracy. Using the IMF’s Monitoring of Fund Arrangements (MONA) database, we conduct the most comprehensive evaluation of IMF forecasts to date for countries in times of crises. We examine 29 macroeconomic variables in terms of bias, efficiency, and information content to find that IMF forecasts add substantial informational value, as they consistently outperform naive forecast approaches. However, we also document that there is room for improvement: two-thirds of the key macroeconomic variables that we examine are forecast inefficiently, and six variables (growth of nominal GDP, public investment, private investment, the current account, net transfers, and government expenditures) exhibit significant forecast biases. The forecasts for low-income countries are the main drivers of forecast biases and inefficiency, perhaps reflecting larger shocks and lower data quality. When we decompose the forecast errors into their sources, we find that forecast errors for private consumption growth are the key contributor to GDP growth forecast errors. Similarly, forecast errors for non-interest expenditure growth and tax revenue growth are crucial determinants of the forecast errors in the growth of fiscal budgets. Forecast errors for balance of payments growth are influenced significantly by forecast errors in goods import growth. The results highlight which macroeconomic aggregates require further attention in future forecast models for countries in crises.

A quasi-Bayesian local likelihood approach to time varying parameter VAR models

The paper establishes a quasi-Bayesian local likelihood (QBLL) estimation methodology for a multivariate model with time varying parameters. The asymptotic validity of the resulting quasi-posterior distributions of the drifting parameters is proven in general and, in the special case of a Gaussian VAR model, a closed form time varying Normal-Wishart expression for the quasi-posterior distribution of the parameters is provided. In addition, this paper develops several Gibbs algorithms, which can sample from a VAR model with a mixture of time varying and time invariant parameters. The proposed estimators differ from existing state space approaches to VAR models in that they estimate parameter time variation nonparametrically, without imposing parametric stochastic processes on the parameters. The QBLL estimators are robust to misspecification of the state equation and exhibit good finite sample performance, even when compared to correctly specified parametric state space models, as illustrated by a Monte Carlo exercise. In addition, we demonstrate that the QBLL approach provides a remedy to the ‘curse of dimensionality’ by accommodating large dimensional VAR systems and delivers improvements in the out-of-sample forecasts of key macroeconomic variables. Finally, the paper makes an empirical contribution to the literature on changing inflation dynamics in the U.S., presenting evidence of a fall in inflation persistence and volatility during the Great Moderation period.

Forecasting with many predictors using Bayesian additive regression trees

AbstractForecasting with many predictors provides the opportunity to exploit a much richer base of information. However, macroeconomic time series are typically rather short, raising problems for conventional econometric models. This paper explores the use of Bayesian additive regression trees (Bart) from the machine learning literature to forecast macroeconomic time series in a predictor‐rich environment. The interest lies in forecasting nine key macroeconomic variables of interest for government budget planning, central bank policy making and business decisions. It turns out that Bart is a valuable addition to existing methods for handling high dimensional data sets in a macroeconomic context.