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Existing empirical evidence suggests that episodes of financial stress (crises) can act as driver of growth of inequality. Consequently, in this study, the authors explore the time-varying predictive power of an index of financial stress for growth in income (and consumption) inequality in the UK. The authors focus on the UK since income (and consumption) inequality data are available at a high frequency, i.e. on a quarterly basis for over 40 years (June, 1975 to March, 2016).

The authors use Wang and Rossi's approach to analyze the time-varying impact of financial stress on inequality. Hence, the method provides a more appropriate inference of the effect rather than a constant parameter Granger causality method. Besides, understandably, the time-varying approach helps to depict the time-variation in the strength of predictability of financial stress on inequality.

This study’s findings point that financial distress correspond to subsequent increases in inequality, with the index of financial stress containing important information in predicting growth in income inequality for both in and out-of-sample periods. Interestingly, the strength of the in-sample predictive power is high post the period of the global financial crisis, as was observed in the early part of the sample. The authors believe these findings highlight an important role of financial stress for inequality – an area of investigation that has in general remained untouched.

Accurate prediction of inequality at a higher frequency should be more relevant to policymakers in designing appropriate policies to circumvent the wide-ranging negative impacts of inequality, compared to when predictions are only available at the lower annual frequency.

The purpose of this paper is to study the evolution of monetary policy uncertainty and its impact on the South African economy.

The authors use a sign restricted SVAR with an endogenous feedback of stochastic volatility to evaluate the sign and size of uncertainty shocks. The authors use a nonlinear DSGE model to gain deeper insights about the transmission mechanism of monetary policy uncertainty.

The authors show that monetary policy volatility is high and constant. Both inflation and interest rates decline in response to uncertainty. Output rebounds quickly after a contemporaneous decrease. The DSGE model shows that the size of the uncertainty shock matters – high uncertainty can lead to a severe contraction in output, inflation and interest rates.

The authors model only a few variables in the SVAR – thus missing perhaps other possible channels of shock transmission.

There is a lesson for monetary policy: monetary policy uncertainty, in isolation from general macroeconomic uncertainty, often creates unintended adverse consequences and can perpetuate a weak economic environment. The tasks of central bankers are incredibly difficult. Their models project output and inflation with relatively large uncertainty based on many shocks emanating from various sources. It matters how central bankers react to these expectations and how they communicate the underlying risks associated with setting interest rates.

This is the first study that looks into monetary policy uncertainty into South Africa using a stochastic volatility model and a nonlinear DSGE model. The results should be very useful for the Central Bank as it highlights how uncertainty, that they create, can have adverse economic consequences.

Portfolio construction and diversification is a prominent challenge for investors. It reflects market agents’ behavior and response to market conditions. This paper aims to investigate the stock-bond nexus in the case of two emerging and two mature markets, India, South Africa, the UK and the USA, using long-term historical monthly data.

To address the issue at hand, copula quantile-on-quantile regression (C-QQR) is used to model the correlation structure. Although this technique is driven by copula-based quantile regression model, it retains more flexibility and delivers more robust and accurate estimates.

Results suggest that there is substantial heterogeneity in the bond-stock returns correlation across the countries under study point to different investors’ behavior in the four markets examined. Additionally, the findings reported herein suggest that using C-QQR in portfolio management can enable the formation of tailored response strategies, adapted to the needs and preferences of investors and traders.

To the best of the authors’ knowledge, no previous study has addressed in a comparative setting the stock-bond nexus for the four countries used here using long-term historical data that cover the periods 1920:08-2017:02, 1910:01-2017:02, 1933:01-2017:02 and 1791:09-2017:02 for India, South Africa, the UK and the USA, respectively.

This paper aims to examine herding behaviour among investors and traders in UK-listed Real Estate Investment Trusts (REITs) within three market regimes (low, high and extreme volatility periods) from the period June 2004 to April 2016.

Observations of investors in 36 REITs that trade on the London Stock Exchange as at April 2016 were used to analyse herding behaviour among investors and traders of shares of UK REITs, using a Markov regime-switching model.

Although a static herding model rejects the existence of herding in REITs markets, estimates from the regime-switching model reveal substantial evidence of herding behaviour within the low volatility regime. Most interestingly, the authors observed a shift from anti-herding behaviour within the high volatility regime to herding behaviour within the low volatility regime, with this having been caused by the FTSE 100 Volatility Index (UK VIX).

The results have various implications for decisions regarding asset allocation, diversification and value management within UK REITs. Market participants and analysts may consider that collective movements and market sentiment/psychology are determinative factors of risk-return in UK REITs. In addition, general uncertainty in the equity market, proxied by the impact of the UK VIX, may also provide a signal for increasing herding-related risks among UK REITs.

Assessing the strength and time variation of spillovers between returns on residential real estate, real estate investment trusts (REITs), stocks and bonds in the United States. Spillovers reduce the benefits of portfolio diversification, especially in crisis times, when asset returns tend to be more correlated.

The Diebold–Yilmaz approach in the time domain and the Baruník–Krehlík methodology in the frequency domain are used. The latter allows distinguishing spillovers generating only short-lived volatility from those with a more persistent effect.

On average, spillovers between housing, stock and bond returns are relatively modest and shocks to stock and bond markets affect housing returns more than the other way round, even though with variations over time. Spillovers in both directions are much stronger between REITs and stocks than between REITs and housing. Shocks originating in the housing market are most persistent, particularly in the aftermath of the subprime crisis.

Housing provides a hedge against volatility in financial (including REITs) markets. However, hedging strategies involving housing need to take into account potential tail events such as the GFC and the investment horizon.

To the best of the knowledge of the authors, this paper is the first to apply the Baruník–Krehlík methodology to real estate price spillovers. Although the Diebold–Yilmaz methodology has been used in several studies on spillovers between residential real estate and financial asset returns, this paper covers a new set of variables and time span.

The purpose of this paper is to examine intentional herding among institutional investors with a particular focus on the technology sector that was the driver of the “New Economy” in the USA during the dot-com bubble of the 1990s.

Using data on technology stockholdings of 115 large institutional investors, the authors test the presence of herding by examining linear dependence and feedback between individual investors’ technology stockholdings and that of the aggregate market. Unlike other models to detect herding, the authors use Geweke (1982) type causality tests that allow authors to disentangle spurious herding from intentional herding via tests of bidirectional and instantaneous causality across portfolio positions in technology stocks.

After controlling information-based (spurious) herding, the tests show that 38 percent of large institutional investors tend to intentionally herd in technology stocks.

The findings support the existing literature that investment decisions by large institutional investors are not only driven by fundamental information, but also by cognitive bias that is characterized by intentional herding.

The purpose of this paper is to assess the efficiency of agricultural production in South Africa from 1970 to 2014, using an integrated two-stage fuzzy approach.

Fuzzy technique for order preference by similarity to ideal solution is used to assess the relative efficiency of agriculture in South Africa over the course of the years in the first stage. In the second stage, fuzzy regressions based on different rule-based systems are used to predict the impact of socio-economic and demographic variables on agricultural efficiency. They are compared with the bootstrapped truncated regressions with conditional α levels proposed in Wanke et al. (2016a).

The results show that the fuzzy efficiency estimates ranged from 0.40 to 0.68 implying inefficiency in South African agriculture. The results further reveal that research and development, land quality, health expenditure–population growth ratio have a significant, positive impact on efficiency levels, besides the GINI index. In terms of accuracy, fuzzy regressions outperformed the bootstrapped truncated regressions with conditional α levels proposed in Wanke et al. (2015).

Policies to increase social expenditure especially in terms of health and hence productivity should be prioritized. Also policies aimed at conserving the environment and hence the quality of land is needed.

The paper is original and has not been previously published elsewhere.

The purpose of this paper is to investigate whether there exist multiple bubbles in the Brazil, Russia, India, China and South Africa (BRICS) stock markets.

In this study, the authors apply the generalized sup Augmented Dickey-Fuller test, a new recursive test proposed by Phillips et al. (2015) and use monthly data on stock price-dividend ratio.

The empirical results indicate that there exist multiple bubbles in the stock markets of the BRICS. Further, the dates of the bubbles also correspond to specific events in the stock markets of these economies. This finding has important economic and policy implications.

The authors declare that this paper is original and has not been published by another journal previously.

This study systematically reviewed existing literature on the impact of economic uncertainty on property performance to highlight focus areas and spur future research amid unprecedented global uncertainty levels. Conceptually, uncertainty levels and environmental dynamism are related to investors' risk judgement and decision-making.

Peer-reviewed journal articles published from 2007 to 2022 were assembled and arranged through the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) protocol. The initial search produced 2,028 results from the Web of Science and Scopus databases, which were rigorously purified for a final dataset of 70 articles. These records were subsequently assessed through content analysis, bibliographic modelling, topic modelling and thematic analysis. Recurring themes were visualised using the VOSviewer software.

The existing literature suggests that economic uncertainty negatively impacts investment volumes, returns and performance. Research has also increased since 2018, with a strong emphasis on the housing sector and developed property markets. Commercial property and emerging markets account for only 10 and 8% of previous research, respectively.

These findings highlight the negative impact of economic uncertainties on property performance and investment volumes, which necessitate careful risk assessment. Given the high susceptibility of emerging and commercial property markets to uncertainty, these markets warrant further research amid ongoing uncertainty concerns across the globe.

Given current unprecedented levels of global uncertainty, the effects of economic uncertainty have received renewed interest. This study synthesised the current understanding of how different property markets respond to increased uncertainty and outlined future research directions to enhance understanding. Themes and relationships were also integrated into a conceptual map summarising the reported effects of economic uncertainty on housing, commercial property, investment and behaviour in the property market.

This paper aims at developing a theoretical model of a world economy characterized by tax evasion. It seeks to analyze whether financial repression can be explained by tax evasion.

The analysis is performed in overlapping generations dynamic general equilibrium endogenous monetary growth models.

The paper shows that higher degree of tax evasion within a country, resulting from a higher level of corruption and a lower penalty rate, yields higher degrees of financial repression.

Financial repression can be explained by tax evasion but under specific conditions.

This is the first attempt to analyze financial repression and tax evasion in an endogenous growth model.