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This paper aims to investigate the integrational properties of real GDP for 125 countries.

The paper applies the Kwiatkowski et al. univariate test and a KPSS‐type univariate test that accounts for multiple structural breaks – a test procedure proposed by Carrion‐i‐Silvestre et al. The panel versions of the KPSS‐type test, proposed by Carrion‐i‐Silvestre et al. with and without structural breaks, are also applied.

The paper finds that, while univariate tests with and without structural breaks provide mixed results on persistence, the panel test suggests that shocks to national output are persistent.

This is a multi‐country study that focuses on both developed and developing countries and uses more recent data to provide new and comparable evidence on the persistence of output.

This paper aims to investigate business network activity patterns and how they change when actors experience tensions.

Four tensions, developed from previous literature, are considered in relation to how they influence activity patterns. A longitudinal case study focusing on the modernization of an international airport illustrates how tensions experienced by actors influence changes in activity patterns.

Results highlight that when tensions in relation to network position are experienced activity patterns are more likely to break and form new patterns. When multiple tensions are experienced within the same period, an old activity pattern is more likely to be broken and the new activity pattern develop.

Contributions in relation to interdependencies between activities heighten the impact of changes leading to the breaking of existing patterns, particularly the importance of coordination activities. These findings are context specific because activity patterns vary according to the industry.

Practical implications indicate that understanding network interdependences within the change process is important, particularly for co-ordination activities. The study informs practitioners about possible outcomes while tensions are experienced. This study found that when actors are experiencing multiple tensions, breaking of activity patterns is more likely to occur while experience less tensions extending existing activity patterns becoming more likely.

Contributions are made in relation to gaps in investigating the business network activity layer and their changes in relation to tensions.

Within a multivariate framework, this study examines the asymmetric and threshold impact of external debt on economic growth in Egypt during the period 1980–2019.

The paper uses a nonlinear autoregressive distributed lag (NARDL) bounds testing approach to cointegration and a vector error-correction model to estimate the short- and long-run parameters of equilibrium dynamics. A multiple structural breaks model is estimated to test nonlinearity in the relationship between external debt and economic growth.

Results of the NARDL model show a robust statistically significant negative long-run impact on economic growth stemming from both positive and negative external-debt-induced shocks. In terms of magnitude, on the one hand, the impact of external-debt-induced negative shocks exceeds that of the positive. In the short and long run, on the other hand, the growth impact of external debt in Egypt is symmetric. There is also support for the nonlinearity hypothesis in which a negative impact on growth of external debt obtains once the threshold level of external debt-to-GDP ratio equals or exceeds 96.7%.

Identifying the threshold level after which external debt becomes harmful to economic growth would help inform policymakers in Egypt about maximum external debt levels that can be sustained without impairing economic growth.

The current study makes a substantial contribution to the extant literature on the debt-growth tradeoffs. It breaks ground by being the first tract that examines, using a NARDL model, asymmetry and nonlinearity of debt-growth tradeoffs in Egypt.

This paper, a case study, aims to consider whether the income ratio and rental ratio tracks the formation of residential housing price spikes and their collapse. The ratios are measuring the risk associated with house price stability. They may signal whether a real estate investor should consider purchasing real property, continue holding it or consider selling it. The Federal Reserve Bank of Dallas (Dallas Fed) calculates and publishes income ratios for Organization for Economic Cooperation and Development countries to measure “irrational exuberance,” which is a measure of housing price risk for a given country's housing market. The USA is a member of the organization. The income ratio idea is being repurposed to act as a buy/sell signal for real estate investors.

The income ratio calculated by the Dallas Fed and this case study's ratio were date-stamped and graphed to determine whether the 2006–2008 housing “bubble and burst” could be visually detected. An ordinary least squares regression with the data transformed into logs and a regression with structural data breaks for the years 1990 through 2019 were modeled using the independent variables income ratio, rent ratio and the University of Michigan Consumer Sentiment Index. The descriptive statistics show a gradual increase in the ratios prior to exposure to an unexpected, exogenous financial shock, which took several months to grow and collapse. The regression analysis with breaks indicates that the income ratio can predict changes in housing prices using a lead of 2 months.

The gradual increases in the ratios with predetermine limits set by the real estate investor may trigger a sell decision when a specified rate is reached for the ratios even when housing prices are still rising. The independent variables were significant, but the rent ratio had the correct sign only with the regression with time breaks model was used. The housing spike using the Dallas Fed's income ratio and this study's income ratio indicated that the housing boom and collapse occurred rapidly. The boom does not appear to be a continuous housing price increase followed by a sudden price drop when ratio analysis is used. The income ratio is significant through time, but the rental ratio and Consumer Sentiment Index are insignificant for multiple-time breaks.

Investors should consider the relative prices of residential housing in a neighborhood when purchasing a property coupled with income and rental ratio trends that are taking place in the local market. High relative income ratios may signal that when an unexpected adverse event occurs the housing market may enter a state of crisis. The relative housing prices to income ratio indicates there is rising housing price stability risk. Aggregate data for the country are used, whereas real estate prices are also significantly impacted by local conditions.

Ratio trends might enable real estate investors and homeowners to determine when to sell real estate investments prior to a price collapse and preserve wealth, which would otherwise result in the loss of equity. Higher exuberance ratios should result in an increase in the discount rate, which results in lower valuations as measured by the formula net operating income dividend by the discount rate. It can also signal when to start reinvesting in real estate, because real estate prices are rising, and the ratios are relative low compared to income.

The graphical descriptive depictions seem to suggest that government intervention into the housing market while a spike is forming may not be possible due to the speed with which a spike forms and collapses. Expected income declines would cause the income ratios to change and signal that housing prices will start declining. Both the income and rental ratios in the US housing market have continued to increase since 2008.

A consumer sentiment variable was added to the analysis. Prior researchers have suggested adding a consumer sentiment explanatory variable to the model. The results generated for this variable were counterintuitive. The Federal Housing Finance Agency (FHFA) price index results signaled a change during a different year than when the S&P/Case–Shiller Home Price Index is used. Many prior studies used the FHFA price index. They emphasized regulatory issues associated with changing exuberance ratio levels. This case study applies these ideas to measure relative increases in risk, which should impact the discount rate used to estimate the intrinsic value of a residential property.

This paper aims to analyze and give directions for advancing research in stock market volatility highlighting its features, structural breaks and emerging developments. This study offers a platform to research the benchmark studies to know the research gap and give directions for extending future research.

The author has performed the literature review, and, reference checking as per the snowballing approach. Firstly, the author has started with outlining and simplifying the significance of the subject area, the review illustrating the various elements along with the research gaps and emphasizing the finding.

This work summarizes the studies covering the volatility, its properties and structural breaks on various aspects such as techniques applied, subareas and the markets. From the review’s analysis, no study has clarified the supremacy of any model because of the different market conditions, nature of data and methodological aspects. The outcome of this research work has delivered further magnitude to research the benchmark studies for the upcoming work on stock market volatility. This paper has also proposed the hybrid volatility models combining artificial intelligence with econometric techniques to detect noise, sudden changes and chaotic information easily.

The author has taken the research papers from the scholarly journal published in the English language only and the author may also consider other nonscholarly or other language journals.

To the best of the author’s knowledge, this research work highlights an updated and more comprehensive framework examining the properties and demonstrating the contemporary developments in the field of stock market volatility.

This paper shows that volatility persistence in GARCH models and spurious long memory in autoregressive models may arise if the possibility of structural changes is not incorporated in the time series model. It also describes a tractable hidden Markov model (HMM) in which the regression parameters and error variances may undergo abrupt changes at unknown time points, while staying constant between adjacent change-points. Applications to real and simulated financial time series are given to illustrate the issues and methods.

This paper aims to examine how consumers evaluate and respond after failing to receive the promotional price for a quantity discount because the minimum purchase requirement (MinPR) is out of reach. Although quantity discounts are effective in terms of increasing sales volume, the outcome of using them is not always positive.

Two 2 × 2 experiments are carried out to test the research hypotheses in the context of apparel shopping.

The results of Experiment 1 demonstrate that offering quantity discounts with a high MinPR (e.g. “4 for 30 per cent off”) can result in greater willingness to buy (WTB) a single product at the full price than offering promotions with a low MinPR (e.g. “2 for 30 per cent off”) in the wake of a missed quantity discount. In other words, the purchase quantity has a positive effect on the consumers’ WTB even when they are not able to take advantage of the discount. However, this relationship weakens when the selection of discounted items is limited (i.e. the scope of the promotion is narrow). The results of Experiment 2 reveal that when the missed quantity discount is based on dollars rather than on the number of pieces (e.g. “Buy $100, get 30 per cent off” vs “Buy four pieces, get 30 per cent off”), the effect of purchase quantity on WTB is enhanced. Finally, perceived closeness of purchase outcome to the MinPR mediates the effect of purchase quantity on WTB.

To maximize internal validity, hypothetical scenarios were used as stimuli rather than an actual consumption experience, and the setting involved only a single product category (clothing). Future work including other types of merchandise and a more natural setting is needed to generalize our findings.

The purchase quantity or MinPR serves as a reference point that influences consumers’ purchase decisions, even those who do not buy enough to qualify for the price reduction. Our findings suggest that retailers should specify a relatively high MinPR for quantity discounts. In addition, proper selection of the promotional scope and discount base will significantly improve consumers’ behavioral reactions when they are not able to take advantage of a quantity discount.

The primary contribution of this article to the marketing literature is that it provides empirical results that shed some light on the situational influences that missing a quantity discount has on the consumer’s WTB a single product at the regular price, and what the mechanisms for the purchase quantity effect might be.

The purpose of this study is to analyze the dynamic causal relationship between foreign direct investment (FDI), gross domestic product (GDP) and trade openness (TO) on a set of five selected South Asian countries.

This study used newly developed bootstrap auto regressive distributed lags (ARDL) cointegration test to examine the long-run relationship among FDI, GDP and TO for selected South Asian countries for 1975–2016.

The economic growth (EG) is significantly related to TO for Bangladesh, India and Sri Lanka and the expansion of TO is crucial for growth in these countries. The results show that all countries (except Bangladesh) found the existence of long-run cointegration between FDI, GDP and TO, whereas FDI is a dependent variable. These results concluded that FDI and TO are contributing to EG in these selected countries.

This study is one of the first attempts to investigate the causal relationship and address the short and long dynamic among FDI, GDP and TO regarding five south Asian countries such as Bangladesh, India, Nepal, Pakistan and Sri Lanka.

This paper investigates the relationship between (1) business cycle and use of personal contacts to obtain job and (2) use of personal contacts to obtain job and wages.

For this, we use data from the Monthly Employment Survey (2002–2015) from Brazil which has detailed information on individual and job characteristics. In addition, we investigate the impact of referrals on wage using quantile regressions.

Time-varying parameter estimates indicate that the relationship between business cycle and use of personal contacts became less countercyclical over time. In general, they show that there is more evidence of a slow changing relationship between personal contacts and the business cycle over time rather than a sudden and discrete one. Using quantile regressions, we observed that, controlling for similar observable characteristics, and including unobserved heterogeneity, wage differences between workers using personal contacts versus workers using others channels disappear. The evidences indicate that workers resort to personal contacts because of valuation of non-pecuniary job characteristics.

The results suggest that, in designing subsidy or affirmative action programs, attention to network effects is important. Social networks can help labor markets run more smoothly by alleviating information frictions.

This study extends the existing literature by providing empirical evidence of the use of personal contacts for the Brazil. Although there are many studies and methods for measuring use of personal contacts, to our knowledge, there are no studies using a time-varying parameters model.