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The purpose of this paper is to examine whether macroeconomic variables have a symmetric or asymmetric effect on stock prices (SP) of Karachi Stock Exchange 100 index in the context of Pakistan. It also examines whether the asymmetric impact of macroeconomic variables on SP has been affected by tail events such as the global financial crisis.

This study uses linear and nonlinear autoregressive distributed lag models for the full sample period as well as in pre- and post-crisis periods. The whole sample period covers the data from June 2004 to June 2016 which include 145 observations in total. The pre-crisis period covers data from June 2004 to December 2007 and the post-crisis period covers the data from January 2009 to June 2016 where these periods include 43 and 90 observations, respectively.

The findings suggest that the relationship between macroeconomic variables and SP is asymmetric in the short run whereas this effect is symmetric in the long run when the whole sample period is selected. However, when pre- and post-crisis periods are selected this effect becomes asymmetric in the long run as well; that is, positive and negative shocks in macroeconomic variables do not affect the SP in the same way.

Investors, governments and other stakeholders are advised to consider the asymmetric behavior of macroeconomic variables and SP while making an investment or other decisions. They may consider the financial crisis as well since the asymmetric behavior of the underlying variables change as a result of the financial crisis.

This study extends previous studies by examining the asymmetric effect of macroeconomic variables and also contributes to the existing literature by discussing how this relationship changes as a result of the financial crisis.

This paper aims to examine whether Indonesian cross-border trade responds asymmetrically to exchange rate volatility (ERV).

An exponential generalized autorgressive conditional heteroscedasticity model is applied to estimate the ERV of Indonesia and ten main trade partners using quarterly data from 2006 to 2020. A nonlinear autoregressive distributed lag estimation is applied to estimate the impact of ERV on cross-border trade. Impacts from the global financial crisis (GFC) of 2008 and the COVID-19 pandemic are covered. Dynamic panel data is used for the robustness test.

In the short-run, ERV significantly affects exports to most of the top partners (positively, negatively or both). In the long run, asymmetric effects occur in Indonesia’s exports to five top destinations. The weakening of the Indonesian Rupiah mainly supports exports in the short term. Imports from top partners are also affected by ERV in both the short run and, to a lesser extent, in the long run. Both the GFC and the COVID-19 pandemic reduced trade: for most cases, in the short run. The dynamic panel model suggests that ERV has asymmetric impact on cross-border trade in the long run.

Exchange rate strategies need to avoid a single-side policy approach and, instead, account for exporter and importer differences in risk behaviour and an asymmetric response to ERV in trade. Policymakers need to consider policies that stabilise the currency.

This study provides evidence that cross-border trade can react asymmetrically to the exchange rate uncertainty and that the impacts of real ERV are asymmetric as well. The authors also apply a dynamic panel that signals that ERV matters in the long run for Indonesian trade with top partners.

The purpose of this paper is to construct a frequency-domain framework to study the asymmetric spillover effects of international economic policy uncertainty on China’s stock market industry indexes.

This paper follows the time domain spillover model, asymmetric spillover model and frequency domain spillover model, which not only studies the degree of spillover in time domain but also studies the persistence of spillover effect in frequency domain.

It is found that China’s economic policy uncertainty plays a dominant role in the spillover effect on the stock market, while the global and US economic policy uncertainty is relatively weak. By decomposing realized volatility into quantified asymmetric risks of “good” volatility and “bad” volatility, it is concluded that economic policy uncertainty has a greater impact on stock downside risk than upside risk. For different time periods, the sensitivity of long-term and short-term spillover economic policy impact is different. Among them, asymmetric high-frequency spillover in the stock market is more easily observed, which provides certain reference significance for the stability of the financial market.

The originality aims at extending the traditional research paradigm of “time domain” to the research perspective of “frequency domain.” This study uses the more advanced models to analyze various factors from the static and dynamic levels, with a view to obtain reliable and robust research conclusions.

Several studies focus on asymmetric impact of shocks on conventional stocks. However, only few studies explore Islamic stocks, but none has examined the asymmetric impact of shocks on Islamic stocks. This study aims to fill the gap by investigating the asymmetric impact of shocks on Islamic stocks. Specifically, it identifies the effect of good and bad news on Islamic stock market. The study also aims to examine the returns and volatility spillover effects across different Islamic markets.

To carry out the empirical analysis, the authors have applied the exponential generalized autoregressive conditional heteroscedasticity (ARCH) model on daily Islamic stock indices of 18 countries. The study covers the period from July 2009 to July 2016. The authors have started their empirical analysis by examining the time series properties and testing the presence of ARCH effects. Further, the authors have applied several post-estimation tests to ensure the robustness of the results.

The results indicate that there is significant leverage effect in Islamic stocks traded in the sampled countries. That is, negative shocks or bad news have stronger effects on Islamic stock returns’ volatility as compared to positive shocks or good news. The authors also found that there are significant mean spillover effects for the examined countries. This finding implies that increased Islamic stock returns in country have significant and positive effects in Islamic stocks’ returns in another other. Similarly, the results regarding the volatility spillover effects suggest that there are significant volatility spillover effects across all examined countries. However, the authors found both positive and negative volatility spillover effects. It should also be noted that in some cases, the authors did not find any significant volatility spillover effect.

The findings of this study have several important policy implications for both investors and policymakers. As the findings suggest that Islamic stock indices are integrated across countries both in terms of returns (mean) and risk (volatility), they are useful for investors to design well-diversified portfolios. The significant volatility spillovers suggest policymakers to design such policy that may help in reducing the adverse effects of increased volatility of Islamic stock of other/foreign countries on the Islamic stocks of the home countries. The significant evidence of the presence of leverage (asymmetric) effects suggest investors to use effective and active hedging instruments to hedge risk, particularly, in bad times.

Unlike other studies on Islamic stocks, this study takes into account the asymmetric effects of positive and negative shocks. Further, the study examines the mean and variance spillover effects for a large panel of countries having Islamic stocks. Finally, several pre- and post-estimation tests are applied to ensure the robustness of the results.

This study examines the roles of cross-sectional dependence, asymmetric structure and country-to-country policy variations in the inflation-poverty reduction causal nexus in selected sub-Saharan African (SSA) countries from 1981 to 2019.

To account for cross-sectional dependence, heterogeneity and policy variations across countries in the inflation-poverty reduction causal nexus, this study uses robust Hatemi-J data decomposition procedures and a battery of second-generation techniques. These techniques include cross-sectional dependency tests, panel unit root tests, slope homogeneity tests and the Dumitrescu-Hurlin panel Granger non-causality approach.

Unlike existing studies, the panel and country-specific findings exhibit several dimensions of asymmetric causality in the inflation-poverty nexus. Positive inflationary shocks Granger-causes poverty reduction through investment and employment opportunities that benefit the impoverished in SSA. These findings align with country-specific analyses of Botswana, Cameroon, Gabon, Mauritania, South Africa and Togo. Also, a decline in poverty causes inflation to increase in the Congo Republic, Madagascar, Nigeria, Senegal and Togo. All panel and country-specific analyses reveal at least one dimension of asymmetric causality or another.

All stakeholders and policymakers must pay adequate attention to issues of asymmetric structures, nonlinearities and country-to-country policy variations to address country-specific issues and the socioeconomic problems in the probable causal nexus between the high incidence of extreme poverty and double-digit inflation rates in most SSA countries.

Studies on the inflation-poverty nexus are not uncommon in economic literature. Most existing studies focus on inflation’s effect on poverty. Existing studies that examine the inflation-poverty causal relationship covertly assume no asymmetric structure and nonlinearity. Also, the issues of cross-sectional dependence and heterogeneity are unexplored in the causal link in existing studies. All panel studies covertly impose homogeneous policies on countries in the causality. This study relaxes this supposition by allowing policies to vary across countries in the panel framework. Thus, this study makes three-dimensional contributions to increasing understanding of the inflation-poverty nexus.

The purpose of this study is to assess the symmetric and asymmetric impact of a measure of policy uncertainty on house permits issued in each state of the USA.

To assess the symmetric effects, the authors use Pesaran et al.’s (2001) linear autoregressive distributed lag (ARDL) approach to error-correction modeling. To assess the asymmetric effects, they rely upon Shin et al.’s (2014) nonlinear ARDL approach to error-correction modeling. Both approaches have the advantage of producing short-run and long-run effects in one step.

The authors find short-run symmetric effects of policy uncertainty on house permits issued in 22 states that lasted into the long run in three states only. However, the numbers were much higher when they estimated the possibility of asymmetric effects of policy uncertainty. Indeed, they found short-run asymmetric effects in 38 states and long-run asymmetric effects in 18 states.

Some previous studies assessed the effects of a measure of policy uncertainty on house prices. In this paper, the authors extend the same analysis to the supply side of the housing market by assessing the effects of policy uncertainty on house permits in each state of the USA.

The primary objective of the paper is to examine the asymmetric Cointegration and asymmetric causality between financial development and poverty alleviation on annual data in Indian context over the period from 1980 to 2019.

First nonlinearity test by Brooks et al. (1999) is applied to ascertain the nonlinear behavior of the variables used. Once the nonlinear behavior of variables is confirmed, asymmetric and nonlinear unit root tests by Kapetanios and Shin (2008) are applied to check for the order of integration of selected variables. Next, nonlinear autoregressive distributed lag model (NARDL) is employed to analyze the asymmetric Cointegration. Finally, Hatemi-j- asymmetric causality tests is applied to work out the direction of asymmetric causality.

The empirical findings document the existence of asymmetries in the short-run as well as long-run between poverty and financial development. The asymmetry reveals that negative financial development shocks leave a more profound impact on poverty alleviation than their positive equivalents. The findings of Wald's test also confirm the presence of asymmetric Cointegration. The asymmetric cumulative dynamic multipliers used to examine the behavior of asymmetries and adjustments with respect to time lend credence to the results calculated using NARDL estimator. This result exhibits the robustness of the model. Furthermore, the result emanating from recently introduced asymmetric causality test reveals a unidirectional asymmetric causality between negative shocks in financial development and poverty. The findings of the present study necessitate the need for investigating asymmetric and nonlinear effects in finance–poverty nexus, which existent literature has completely neglected, in order to have relevant policy conclusions.

The study used “Per capita consumption expenditure” as a measure for poverty due to lack of continuous time series data on headcount ratio. In future, researchers can extend this study by incorporating headcount ratio as a measure of poverty in their respective works. There is further scope of research on this issue by finding out the impact of formal and informal sources of credit on poverty separately. A panel data study for developing countries over a period of time could further confirm/negate the findings of the present study.

To the best of the authors’ knowledge none of the studies in Indian context has scrutinized asymmetric and nonlinear impact of financial development on poverty. To dredge up asymmetric structures at work, the authors have used the highly celebrated NARDL estimator. To enrich the existent body of knowledge along the lines of asymmetric (nonlinear) linkages, the authors have also used recently introduced asymmetric causality test by Hatemi-j-(2012) to find out the direction asymmetric causality.

This study aims to explore how the “new normal” induces the dynamics in the asymmetric relationship between service quality attributes and customer satisfaction.

This study analyzes online reviews for hotels in New York City. The authors use multi-attribute models to examine how a situational factor – the COVID-19 outbreak – creates dynamics in the asymmetric effect of service quality attributes on customer satisfaction. Then, the authors examine the change in these dynamics over time after adjusting to the “new normal.”

The COVID-19 pandemic has introduced dynamics into the asymmetrical relationship between hotel service attribute performances and customer satisfaction. The pandemic magnified the asymmetric influences of particular attributes on satisfaction in the hospitality industry. In addition, the findings indicate the changes in such dynamics over time.

The findings emphasize that hotel managers should consider situational factors when understanding customer satisfaction. Particularly, this study suggests developing tailored strategies for responses during the COVID-19 pandemic. Hotel managers need to address changing customer expectations of service attributes to overcome unprecedented difficulties because of the limitations and new needs imposed during the pandemic.

This study contributes to the hospitality literature with an understanding of the significance of situational factors in asymmetric analysis.

This paper aims to examine the asymmetric impact of the oil price increase and decrease on stock returns at the firm level.

To ascertain the impact oil price can exert on the stock price at the firm level, this study uses panel structural vector auto regression with various linear and nonlinear measures of oil price shock on a data set, containing 1,168 firms listed in Indian stock markets. This study also considers stock index returns, Fama-French factors and inflation as control variables.

This paper finds evidence that at firm level, net oil price increase and decrease have an asymmetric impact on stock returns. Other oil price shock measures, namely, shock because of oil price increase and decrease, do not show any sign of asymmetric impact on stock returns.

The comparison of firm-level return on its response towards oil price fluctuation can give valuable insights into a firm’s features.

This paper aims to investigate asymmetric pricing behaviour and impact of coronavirus (Covid-19) pandemic shocks on house price index (HPI) of Turkey and Kazakhstan.

Monthly HPIs and consumer price index (CPI) data ranges from 2010M1 to 2020M5 are used. This study uses a nonlinear autoregressive distributed lag model for empirical analysis.

The findings of this study reveal that the Covid-19 pandemic exerted both long-run and short-run asymmetric relationship on HPI of Turkey while in Kazakhstan, the long-run impact of Covid-19 pandemic shock is symmetrical long-run positive effect is similar in both HPI markets.

The main limitations of this study are the study scope and data set due to data constraint. Several other macroeconomic variables may affect housing prices; however, variables used in this study satisfy the focus of this study in the presence of data constraint. HPI and CPI variables were made available on monthly basis for a considerably longer period which guaranteed the ranges of data set used in this study.

Despite the limitation, this study provides necessary information for authorities and prospective investors in HPI to make a sound investment decision.

This is the first study that rigorously and simultaneously examines the pricing behaviour of Turkey and Kazakhstan HPIs in relation to the Covid-19 pandemic shocks at the regional level. HPI of Kazakhstan is recognized in the global real estate transparency index but the study is rare. The study contributes to regional studies on housing price by bridging this gap in the real estate literature.