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The purpose of this paper is to investigate the impact of a consumer confidence shock on GDP and different types of consumer spending during a slack state as well as a non-slack state of an economy.

The authors use the US quarterly data from 1960Q1 to 2014Q4 and apply Jorda’s (2005) local projection method to compute the impulse responses of macroeconomic variables to a consumer confidence shock. The local projection method allows us to include non-linearities in the response function.

In general, the response of output, following a consumer confidence shock, is similar in slack and non-slack states and indicate that an unfavorable confidence shock is contractionary. However, the intensity and duration of impact of a confidence shock on different components of spending are state dependent. Overall, a negative confidence shock appears to have a stronger impact on non-slack time than on a slack time.

Policy makers should be careful about undertaking a policy action that may affect consumer confidence adversely, particularly during an economic good time. An adverse confidence shock can trigger a downfall in a well-functioning economy and the dampening effect may last for several quarters before the economy rebounds.

US economy is subject to fluctuations; however, the literature on the impact of confidence shock in different economic states is limited. The incremental contribution of this paper is that it investigates how the consumers respond to the confidence shock in a state-dependent model. Furthermore, the authors use a more robust and alternative estimation method that tackles any non-linear problems.

This paper aims to examine the effects of fiscal policy associated with increases in government expenditures, tax revenue and budget deficit on the South African economy.

Structural VARs based on the Blanchard‐Quard decomposition identification scheme were used in the empirical analysis. With the aid of quarterly data covering the period 1990:1 to 2008:4, the identified true models are used to estimate various impulse‐response functions. The impulse‐response functions represent the responses of real output and interest rates to shocks from tax revenue, budget deficit and government consumption and investment expenditures.

The results suggest that the fiscal policy instruments have varied effects on output and interest rates. The effect of the fiscal policy on output appears to be quite modest but persistent; however, the response from interest rate is temporary and substantial most cases.

The debate on the efficacy of fiscal policy in stimulating growth seems to have assumed new prominence in the wake of the recent global financial crisis. This paper contributes to the discourse from a South African focused empirical effort. Other fiscal policy authorities may find the paper valuable.

What would have been the hypothetical effect of monetary policy shocks had a country never joined the euro area, in cases where we know that the country in question actually did join the euro area? It is one thing to investigate the impact of joining a monetary union, but quite another to examine two things at once: joining the union and experiencing actual monetary policy shocks. The authors propose a methodology that combines synthetic control ideas with the impulse response functions to uncover dynamic response paths for treated and untreated units, controlling for common unobserved factors. Focusing on the largest euro area countries, Germany, France, and Italy, the authors find that an unexpected rise in interest rates depresses inflation and significantly appreciates exchange rate, whereas gross domestic product (GDP) fluctuations are less successfully controlled when a country belongs to the monetary union than would have been the case under the independent monetary policy. Importantly, Italy turns out to be the overall beneficiary, since all three channels – price, GDP, and exchange rate – deliver the desired results. The authors also find that stabilizing an economy within a union requires somewhat smaller policy changes than attempting to stabilize it individually, and therefore provides more policy space.

Recently, fractional differential equations have been used to model various physical and engineering problems. One may need a reliable and efficient numerical technique for the solution of these types of differential equations, as sometimes it is not easy to get the analytical solution. However, in general, in the existing investigations, involved parameters and variables are defined exactly, whereas in actual practice it may contain uncertainty because of error in observations, maintenance induced error, etc. Therefore, the purpose of this paper is to find the dynamic response of fractionally damped beam approximately under fuzzy and interval uncertainty.

Here, a semi analytical approach, variational iteration method (VIM), has been considered for the solution. A newly developed form of fuzzy numbers known as double parametric form has been applied to model the uncertainty involved in the system parameters and variables.

VIM has been successfully implemented along with double parametric form of fuzzy number to find the uncertain dynamic responses of the fractionally damped beam. The advantage of this approach is that the solution can be written in power series or compact form. Also, this method converges rapidly to have the accurate solution. The uncertain responses subject to impulse and step loads have also been computed and the behaviours of the responses are analysed. Applying the double parametric form, it reduces the computational cost without separating the fuzzy equation into coupled differential equations as done in traditional approaches.

Uncertain dynamic responses of fuzzy fractionally damped beam using the newly developed double parametric form of fuzzy numbers subject to unit step and impulse loads have been obtained. Gaussian fuzzy numbers are used to model the uncertainties. In the methodology using the alpha cut form, corresponding beam equation is first converted to an interval-based fuzzy equation. Next, it has been transformed to crisp form by applying double parametric form of fuzzy numbers. Finally, VIM has been applied to solve the same for the general fuzzy responses. Various numerical examples have been taken in to consideration.

Housing market is predominantly driven by supply and demand, and the measurement of housing supply plays a crucial role in understanding market dynamics. One such measure is the number of building permits (BPs) issued. Despite the importance of BPs as an economic indicator, direct links have yet to be drawn between BP and housing value index (HVI). The purpose of this paper is to establish links between HVI and BP.

Trials were conducted using data at the national, state and metropolitan statistical area (MSA) levels. For each trial, the Granger causality test was used first to identify causal relationships between HVI and BP. Subsequently, the vector autoregression model was implemented in an attempt to observe impulse–response relationships and to create a forecast for HVI.

Bidirectional causal relationships were observed between HVI and BP at the national, state and MSA levels. The number of issued BPs proves to be an indicator for HVI. Impulse response functions indicate that HVI responds negatively to an increase in BP in the short term of 4–7 months but positively to an increase in BP with a lag of 10–12 months.

To the best of the authors’ knowledge, this paper is the first in the body of knowledge that establishes the number of issued BPs as an indicator for housing value. The results drawn using impulse–response function are also novel and had not been observed in previous studies.

This paper investigates the dynamic relationship between the trade-weighted dollar exchange rates and the oil prices in the world market. Monthly data during 1980–2017 are used for this purpose.

The symmetric and asymmetric generalized impulse response functions are estimated for these important economic indicators.

The empirical findings show that if the dollar rate increases (i.e. the dollar depreciates), the oil price will increase. The reverse relationship is also supported empirically meaning that an increase in the oil price will results in a significant depreciation of the dollar rate. Based on the asymmetric impulses responses, it can also be claimed that the negative interaction is only significant for the positive changes and not for the negative ones. Thus, the underlying variables are negatively interrelated only for the positive shocks since a negative shock from any variable does not seem to have any significant impact on the other variable. These results have implications for cross hedging of price risk.

To the best knowledge, this is the first attempt to investigate the relationship between the dollar weighted exchange rate and the oil pieces via the asymmetric impulse response functions. Both of these variables and their interactions are very important for investors as well as policy makers worldwide.

This study undertakes a comprehensive investigation into the far-reaching repercussions of Covid-19 stimulus packages and containment policies on stock returns, meticulously examining a diverse array of 14 distinct markets.

This study employed the Panel SVAR model to analyze the relationships between various policies and stock market performance during the Covid-19 outbreak. The sample comprises 5432 daily observations spanning from December 2020 to January 2022 for the 14 selected markets, with missing data excluded.

The findings reveal three consistent impacts across all 14 markets. Firstly, stock returns immediately reversed and decreased within a day when Governments tightened containment policies. Secondly, economic stimulus packages led to a fall in stock returns. Thirdly, an increasing death rate caused the stock return to decrease in the following two days. These findings are supported by the uniform impulse responses in all three shocks, including common, composite and idiosyncratic shocks. Furthermore, all inverse root tests satisfy the stability conditions, indicating the stability and reliability of Panel SVAR estimations.

One vital implication is that all government decisions and measures taken against the shock of Covid-19 must consider economic impacts to avoid unnecessary financial losses and support the effective functioning of stock markets during similar shocks. Secondly, investors should view the decline in stock returns due to Covid-19 effects as temporary, resulting from anxiety about the outbreak. The study highlights the importance of monitoring the impact of policies on financial markets and the broader economy during crises. Overall, these insights can prove helpful for investment decisions and policymaking during future crises.

This study constitutes a noteworthy addition to the literature on behavioural finance and the efficient market hypothesis, offering a meticulous analysis of the multifaceted repercussions of Covid-19 on market interactions. In particular, it unveils the magnitude, duration and intricate patterns of market volatilities linked to significant shock events, encompassing a comprehensive dataset spanning 14 distinct markets.

The commodity and equity derivatives have a close resemblance between them in trade practices and mechanisms, which makes it easy for the investors to combine these two assets classes for building up their portfolio. The diversification of investment among asset classes builds some relation between them. The integration of market within a country is necessary to bring in a smooth and balanced economic growth. Thus, the purpose of this paper is to examine the spillover between the equity and commodity futures markets which will be helpful not only for the investors but also for the policy makers, producers and the regulators.

To examine the spillover between the equity and commodity market, the major benchmarking indices of these markets, namely COMDEX of MCX, Dhaanya of NCDEX and NIFTY 50 of NSE, were chosen. NIFTY 50 index was chosen as representative of equity market due to its composition of most active constituent stocks than any other broad market index of Indian stock market. As the commodity market indices are not been traded, their constituent commodities were taken for the study. Thus, 11 MCX-COMDEX constituents such as Gold, Silver, Copper, Zinc, Aluminum, Nickel, Lead, Crude oil, Natural gas, Kapaskhali and Mentha oil and eight NCDEX-Dhaanya constituents such as Castor seed, Chana, Cotton seed oilcake, Jeera, Mustard seed, Refined soy oil, Turmeric and Wheat futures prices were taken against the NIFTY 50 futures prices with daily trading data for ten years starting from January 1, 2006 till December 31, 2015 to analyze their spillover effect. The return series data were used to test the spillover between equity and commodity futures market as it gives the crux of investors’ diversification through the Vector Autoregression (VAR) model and verified with Impulse Response Function by testing the null hypothesis, H₀, that there is no return spillover between the equity and commodity futures market.

The investors move from equity to commodity when there is a threat in equity market and vice versa, thereby diversify their risk for those commodities which are vulnerable to global and domestic pressures in the economy. Investigating the spillover between equity and commodity market gives an insight of market integration effect. A nation can achieve its economic growth easily when its markets are integrated.

The commodity indices are still notional indices in the market; therefore, individual constituent commodities of commodities indices were considered with the benchmarking equity futures index, which is one of the limitations of the study.

The integration of market within a country is necessary to bring in a smooth and balanced economic growth.

Most of the past studies dealt only with few commodities and equities and not with the broad-based benchmarking indices. This paves way for enquiry into the commodity and equity markets integration with the major constituent commodities traded in the economy. Hence, this paper looks into the presence of spillover between the equity and commodity markets. The VAR model is verified with the impulse response function which explains the reaction of any dynamic system in response to a pulse change in another. The impulse response function is presented graphically for easy and better understanding.