Impulse response analysis in conditional quantile models with an application to monetary policy

Recent events have highlighted the potential importance of nonlinear efiects of flscal variables (notably debt and deflcits) on interest rates: While in times when government solvency is not a concern the standard crowding-out efiects are of moderate magnitude, in times when default risk becomes an issue the interest rate efiects can become very large. This paper provides new evidence on the magnitude of these efiects. For the case when default risk is not a concern, it uses an arbitrage-free term structure model to estimate the dynamic efiects of flscal policy shocks on interest rates along the entire maturity spectrum. For the case when default risk becomes a concern (thereby violating a central assumption of the term structure model), I present evidence based on EMU government bond spread regressions on time-varying efiects of national flscal policies on spreads as well as the time-varying sensitivity of yield spreads to international risk aversion as a function of the state of flscal policy. JEL classiflcation: E6, H6.

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] The 2007-2009 economic events have renewed interests in the relationship between the financial sector and the macroeconomy and suggested that shocks originated in the financial sector may be a potential source of business cycle fluctuations. In this regard, this dissertation focuses on quantifying and assessing the role of shocks originated from the financial sector in driving business cycle fluctuations and how monetary policy could possibly respond from a welfare prospective. The dissertation consists of three chapters. The first chapter attempts to model the relationship between the financial sector and the macroeconomy theoretically. Specifically, I build a dynamic stochastic general equilibrium (DSGE) model by incorporating a financial sector with frictions between investors and banks. The existence of such frictions affect the healthiness of the financial sector and increase its riskiness, whereas would not affect those of the non-financial sector by much. I regard this type of frictions as supply-side financial shocks that are originated in the financial sector. Under this framework, the external finance premium in the financial sector can be determined endogenously. To study how the financial shocks would affect the dynamics of the model, impulse responses are used to show that the inclusion of those financial shocks yield larger amplification effects. Thus the model is able to generate higher volatility in aggregate outcomes, especially in the financial sector. This provides theoretical grounds to study the role of supply-side financial shocks for the next two chapters. Chapter two seeks to quantify empirically the effects of the financial shocks on the macroeconomy in a structural vector autoregression (SVAR) model. Based on the model implications derived from Chapter one, two types of financial shocks can be discriminated|the demand-side financial shock that comes from the entrepreneurial sector and the supply-side financial shock that comes from the financial sector. The identification strategy is that these two types of shocks affect the standards deviation of the equity returns in financial and entrepreneurial sectors in opposite directions. The overall SVAR results show that the effects of financial shocks on the real economic activities are non-trivial, although not major. In particular, the supply-side financial shocks originating from the financial sector explain a non-negligible part of the variabilities for the key macro variables; whereas for the financial variables, they are the main drivers, especially during the 2007-2009 crisis period. Chapter three studies how monetary policy should respond to this type of supplyside financial shocks from a prospective of social welfare. In particular, I consider a Taylor-type monetary policy rule augmented with a financial variable|the external finance premium. By doing so, it allows the central bank to react to the changes in the riskiness of the financial sector, in addition to the conventional output and inflation targets. The welfare results show that it is optimal for the central bank to respond to the financial variable. In other words, when there are shocks originated in the financial sector, the riskiness of the financial sector increases, and so do the external financing costs and the external finance premium in the financial sector. The banks' balance sheet conditions worsen and the central bank should cut its policy rate. The welfare analysis also implies that the inflation stabilization is still the most important target of the central bank, which in line with the literature that emphasizes the importance of inflation targeting.

In this study the interdependence between Iran, its major trading partners and the United States is investigated using vector autoregression, generalized impulse response function and generalized variance decomposition techniques, introduced by Pesaran and Shin (1998). These techniques have an advantage over the commonly used impulse response and variance decomposition procedures in that they are insensitive to the ordering of the countries considered and hence, they produce more reliable results. The countries included in the sample, besides Iran are, France, Germany, Spain, Japan, South Korea, Brazil, Italy and the United States. The direction, strength, durability and stability of the effect of shocks in one market on the return patterns of the other markets are examined. The findings are 4-fold. First, the effect of past own market shocks on current behaviour is significant, beyond the first month, in most cases. Second, the own effect is stronger for the emerging markets such as Iran and Brazil, than the industrialized countries. Third, cross-country effects are short-lived for Brazil, Korea and Japan, but durable in the case of Iran, Germany, Spain and the United States. Fourth, in terms of breadth and strength, cross-country effects exhibit differential degrees of interdependence and asymmetry. The observed lack of integration between the Iranian market and the industrialized world makes it less vulnerable to the effect of shocks in the latter countries but it also deprives it from the flow of funds that could spur economic development and growth.

Nonparametric estimation of conditional quantile functions in the presence of irrelevant covariates

Monetary shocks and asymmetric effects in an emerging stock market: The case of China

The policy rate is a crucial monetary policy tool used by central banks to control economic conditions. Its main channel works via a transmission mechanism in which shocks to the policy rate proliferate through the financial system, which then affects the real economy. This study looks at how monetary policy affects the Thai economy and how it works by using a Factor-Augmented Vector Autoregressive (FAVAR) model, which can include both visible and hidden factors in the analysis, unlike traditional VAR methods. To achieve the objective of this study, monthly data from the Bank of Thailand database for the period between January 2011 and December 2023 were collected and analyzed using Principal Component Analysis, Vector Autoregressive technique, Granger causality tests, and impulse response analysis. The results indicate that interest rate hikes have temporary adverse effects on consumer confidence, retail sales, and asset prices. In addition, the findings show the interplay between interest rate shocks and labor markets, represented by worker outflow, employment levels, and job vacancies. The results also reflect the effective transmission of monetary policy through the money market channel, as market interest rates were aligned with the policy rate shock. These results suggest that monetary policy should be implemented in a balanced manner while considering the interconnections between various aspects of the economy. These results justify some supportive fiscal and labor market policies to promote consumption and reduce the adverse effects of monetary policy tightening.

This paper studies the effect of structural oil price shocks on China’s investor sentiment using the Bayesian inference structural vector autoregression (VAR) model by Baumeister and Hamilton (2019). We find that oil supply shocks followed by consumption demand shocks have positive and persistent effects on China’s investor sentiment, whereas aggregate and inventory demand shocks have only temporary effects. The effects of these shocks are transmitted mainly by affecting investor’s confidence in domestic economic fundamentals and the international economic environment. Furthermore, oil price shocks also induce different trading motivations in the stock market.

In this article, we analyse the impact of fiscal shocks on the Indian economy using structural vector auto-regression (SVAR) methodology. The study uses quarterly data for the period 1997Q1–2009Q2. Two different identification schemes have been used to assess the effects of shocks on government spending and tax revenues on output. The recursive scheme is based on the Cholesky decomposition and the second identification scheme of Blanchard & Perrotti’s (1999) technique of using information on the tax system to identify the SVAR model. We find that the impulse responses obtained from both identification schemes behave in a similar fashion but the values of the multipliers differ. Also, the shock-to-tax variable has a bigger impact on gross domestic product (GDP) than the government spending shock. In the extended four variable VAR model, the effects of fiscal shocks on private consumption has been assessed using the recursive identification scheme. Findings indicate that the tax variable has a larger impact on private consumption compared to the government spending variable. In the short run, the impact of expansionary fiscal shocks follows the Keynesian tradition but the long-run response is mixed. JEL Classification: C32, E32, E62

The paper contains a series of complex analyses on the study of typologies of economic crises and can bring a significant contribution to the literature in determining the effects of external factors on economic growth, taking into account the distinct characteristics of the periods of decline. The work includes Hodrick-Prescott filtering techniques for characterizing business cycles in three Central and Eastern European countries and the Structural Vector Autoregression (SVAR) technique is used to analyze the impact of external shocks on economic growth over two distinct time-horizons. External shocks such as external debt, external interest rate, external output, producer price index and real interest rate were taken into account. For each economy analyzed, the impact of the two types of economic crisis was observed, namely financial crisis and health crisis, and two time-horizons were defined for each complete economic cycle. Over these two time-horizons, the impact of external shocks on economic growth has been assessed. There has been a general decrease in the effects of shocks in the second time-horizon, in which the most severe values of economic growth are associated with the health crisis, compared to the time-horizon associated with the financial crisis. It has also been observed that, in the case of both Hungary and Romania, the responses of economic growth to external shocks are faster compared to the Czech economy. Moreover, external production is the factor that explains most of the variance in the economic growth rate in the first time-horizon, while in the second, one of the most influential indicators is the external production price index, which has been severely affected by the slowdown in the global production process.

One way to analyze the impact of commodity price shocks on monetary policy is to think about short-term interest rates set by Fed according to the Taylor rule. Taylor (1993) suggested a policy reaction function for moderating short-term interest rates to achieve the two-fold goals of stabilizing economic growth in the short-term and inflation in the long-term. One important question is why monetary policy makers focus on core inflation instead of headline inflation. Therefore, the main goal of this research article is to study the pattern of monetary policy responses to commodity price shocks derived from an impulse response function (IRF). To do this, we first estimate two individual Taylor rules based on core and headline consumer price index (CPI) inflation by using real-time data of the US economy for the Greenspan years from 1987 to 2006 and predict the residuals. Then, we estimate two regressions for core and headline CPI inflation as our two individual dependent variables against some independent variables including commodity price shocks, and the Taylor rule residuals. At the end, we predict the monetary policy responses to commodity price shocks by using IRF analysis in multivariate systems of a vector autoregression (VAR) model.

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This study examines the impact of monetary and fiscal policy shocks on Romania, a former communist economy transitioning toward a functional market system. The research employs a structural vector auto regression (SVAR) model that integrates both fiscal and monetary policy variables, extending previous models by incorporating the short-term interbank interest rate as a key monetary policy indicator. The findings indicate that monetary policy plays a crucial role in controlling inflation in the medium term, while fiscal policy shocks - represented by government expenditure and revenue changes - exert marginal effects on macroeconomic indicators. Additionally, fiscal policy decisions influence monetary policy responses, prompting immediate central bank actions. These insights are particularly relevant in the current economic landscape, marked by geopolitical instability and inflationary pressures. The study contributes to the ongoing discourse on policy coordination in emerging economies, emphasizing the necessity of a balanced policy mix for macroeconomic stability.

We study the effects of Chinese monetary policy shocks on China's major trading partners in East and South‐East Asia by estimating structural vector autoregressive (SVAR) models for six economies in the region. We find that a monetary expansion in Mainland China leads to an increase in real GDP (temporary) and the price level (permanent) in a number of economies in our sample, most notably in Hong Kong and the Philippines. The impact could result from intertemporal substitution present in a general equilibrium framework, which allows for positive domestic impacts of foreign monetary expansions. Our results emphasize the growing importance of China for its neighbouring economies and the significance of Chinese shocks for the design of monetary policy in Asian economies.

In this article, a new generalization of the Topp-Leone distribution with a unit interval, namely Mixed Topp-Leone-Kumaraswamy distribution is defined and studied. The mathematical properties of this mixing distribution are described. Moments, quantile function, R?nyi entropy, incomplete moments and moments of residual are obtained for the new Mixed Topp-Leone - Kumaraswamy distribution. The maximum likelihood (MLE), Crans (CM) , Percentile (PM) and Particle Swarm Optimization(PSO) estimators of the parameters are derived. The percentile Method is more efficient method as compred to the others. Two real data sets are used to illustrate an application and superiority of the proposed distribution.

Oil price shocks in the age of surging inflation