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The paper aims at analyzing the co-movements between stock returns and oil prices (West Texas Intermediate, Brent) controlling or not for COVID-19.

It uses continuous wavelet transforms and wavelet coherence over the period July 19, 2019 to August 16, 2021 based on daily data. Continuous wavelet transforms provide an over complete representation of stock returns signals by letting the translation and scale parameters of the wavelets vary continuously.

There are not significant evidence supporting the fact that the COVID-19 has altered the relationship between stock returns and oil prices except perhaps in the case of South Africa. In fact, Southern African Development Community stock markets react more to oil prices than to health shock such as the COVID-19.

The findings of the study are original and have not been published anywhere prior.

The purpose of this paper is to examine the response of Travel & Leisure (T&L) stocks of some advanced economies (the USA and United Kingdom) as well as Europe to uncertainty due to pandemics and epidemics. The motivation for the study is derived from the expectation that pandemics and epidemics which are infectious would limit activities and events that require physical interactions such as those associated with T&L, and therefore, returns on related investments may decline during this period.

The authors formulate a model in line with Westerlund and Narayan (2012, 2015) where uncertainty due to infectious diseases is included as a predictor in the valuation of T&L stocks while also controlling for endogeneity bias (for omitted variables bias), conditional heteroscedasticity effect (typical of high frequency data) and persistence (typical of most financial and economic time series).

The authors’ results suggest that contrary to the negative impact of previous cases of pandemics and epidemics on the T&L stocks, the behavior of these stocks during COVID-19 pandemic is modest owing to the positive nexus between equity market volatility due to infectious diseases (EMV-ID) (our proxy for pandemics and epidemics) and the T&L returns during the COVID-19 period. The authors maintain that investors in this market need not panic as the market tends to be resilient to pandemics over time albeit with a lower resilience during daily trading. The results leading to this conclusion are robust to alternative measures of the COVID-19 pandemic.

The peculiarity of this paper on T&L stocks is premised on the introduction of the new datasets for infectious diseases, and the need to include the COVID-19 pandemic given its peculiarity. Essentially, we utilize the Baker et al. (2020) dataset which captures all the pandemics including COVID-19 and a complementary dataset on the COVID-19 pandemic using an alternative approach.

Given the systemic nature of climate change, there are many interdependencies between its primary components and feedback loops, emphasising the need to simultaneously consider the stock market implications of physical and transitional climate-related risks. More importantly, carbon emissions are expected to be reduced through various transition pathways. However, transitional climate risks have been validated as capable of predicting stock market behaviour, hence the motivation for the role of technology shocks.

We use a GARCH-MIDAS model to examine the relationship between climate change and stock return volatility since it enables data analysis at various frequencies within the same framework. We employ a novel dataset to track technology shocks, and the study spans decades of data from 1880 to 2018.

We find that the relationship between climate change and stock return volatility is episodic and varies with different degrees of intensity of high-temperature anomalies and technology shocks. Our results suggest that policy actions should include investing in climate technologies to reduce greenhouse gas emissions and encouraging investment in eco-friendly assets.

There has been little or no consideration for the probable complementary effects of physical and transition climate-related risks on stock markets. Hence, the novelty in the context of this study is the hypothesis that transitional risks, if explored from the point of view of technological innovations, can moderate the stock market’s vulnerability to physical climate risks.

This study forecasts the government expenditure components in Nigeria, including recurrent and capital expenditures for 2021 and 2022, based on data from 1981 to 2020.

The study employs statistical/econometric problems using the Feasible Quasi Generalized Least Squares approach. Expenditure forecasts involve three simulation scenarios: (1) do nothing where the economy follows its natural path; (2) an optimistic scenario, where the economy grows by specific percentages and (3) a pessimistic scenario that defines specific economic contractions.

The estimation model is informed by Wagner's law specifying a positive link between economic activities and public spending. Model estimation affirms the expected positive relationship and is relevant for generating forecasts. The out-of-sample results show that a higher proportion of the total government expenditure (7.6% in 2021 and 15.6% in 2022) is required to achieve a predefined growth target (5%).

This study offers empirical evidence that specifically requires Nigeria to invest a ratio of 3 to 1 or more in capital expenditure to recurrent expenditure for the economy to be guided on growth.

This study aims to construct alternative models to establish the dynamic nexus between inflation and housing prices by estimating the short- and long-run relationship between housing prices and inflation for 15 OECD countries from 1980Q1 to 2022Q4. Furthermore, the authors examined this association using the core and headline inflation and price-income and price-rent ratios as proxies for inflation and housing prices, respectively.

The authors use the panel autoregressive distributed lag technique to examine the nexus between housing prices and inflation to capture the distinct characteristics of the sample countries, estimate various short-run and long-run dynamics cum separate analyses for turbulent and calm periods in the relationship between housing prices and inflation.

Changes in housing prices have a greater impact on core inflation than headline inflation. Overall, the authors establish a positive (negative) relationship between housing prices and core inflation in the long run (short run) based on alternative proxies of housing prices. However, this connection tends to be less significant for headline inflation and episodic over smaller samples, as it seems stronger during calm periods than turbulent ones.

To the best of the authors’ knowledge, the authors are the first to examine the association between housing prices and inflation by demonstrating how these variables behave during calm and turbulent periods.

This study aims to contribute to the literature on migration by examining the nexus between migration-related fears and housing affordability in France, Germany, the UK and the USA using new datasets for migration-related fears.

This study adopts the feasible quasi-generalized least squares approach wherein a predictor can be isolated in the estimation process. Thus, rather than specifying a multi-predictor model that may also lead to parameter proliferation, a single-predictor model (for the predictor of interest) is formulated while also accounting for other salient features resulting from suppressing other important factors that may not be of interest to the current study. Such salient features include persistence, endogeneity and conditional heteroscedasticity issues.

Overall, the results show heterogeneous responses of housing affordability to migration fears across the four developed countries, as the latter deteriorates housing affordability in Germany and the USA and improves it in France and the UK. Similarly, the GFC makes housing less affordable in all four countries as low interest rate passes the mediation test in the nexus. The results, especially for low interest rates, are robust to different uncertainty measures.

As is often the case with economic phenomena, no single model can capture all the factors influencing an economic variable. Thus, besides examining the nexus between migration fears and housing affordability, the authors also account for the role of GDP per capita, given the influence of population and income dynamics on housing affordability. However, incorporating GDP per capita alone does not substantially enhance the model’s ability to predict housing affordability. Future research should explore additional macroeconomic and social factors, such as human capital development, to further enhance this subject.

The findings have significant implications for policymakers regarding the use of low interest rates to counteract the adverse effects of migration-related fear on housing affordability. Specifically, to mitigate the potential negative impact of migration and the associated fear on housing affordability, monetary authorities could adopt a more accommodative stance on mortgages. By allowing real estate investors to obtain loans at lower rates, this approach would help increase housing supply and reduce the housing gap exacerbated by migration influx.

The values of this study lie in its examination of housing affordability in relation to migration fears from both the demand and supply sides of the market. Furthermore, the analyses are conducted to cover out-of-sample forecast evaluation as in-sample predictability may not guarantee out-of-sample prediction.

The issue of housing affordability is a serious concern, as it affects households’ ability to cover housing expenses without sacrificing other essential needs. However, housing affordability is not solely dependent on economic conditions. The consequences of climate change, such as extreme weather events can worsen the housing crisis by reducing the supply of affordable housing and driving up costs. Therefore, the purpose of this paper is to investigate how in addition to economic conditions, climate change affect the affordability of housing in the USA using state-level data covering the 50 states in the country.

This study used a panel autoregressive distributed lag model to estimate short- and long-term effects and analyzed economic periods before and after the global financial crisis. This study also divided the states into two regions, the hottest and coldest, to examine differences in housing affordability.

The findings reveal some crucial facts about housing affordability concerning economic conditions and climate change. The study shows result that suggests better economic conditions lead to increased housing affordability, particularly in colder regions. Additionally, climate change positively affects housing affordability in the short term. Finally, this study confirms the important role of interest rates in the relationship between economic conditions and housing affordability.

The review of existing works indicates that studies on housing concerning economic conditions and climate change at disaggregated levels are very scarce. As a result, this study pays attention to investigating the connection between housing affordability and economic conditions for 50 states in the USA. Additionally, this study makes some extensions by examining the role of climate change and how interest rates could mediate in the nexus given either improved or depressed economic conditions.

This study aims to construct alternative models to establish the dynamic relationship between exchange rates and housing affordability by estimating both the short- and long-run relationship between exchange rates and housing affordability for 18 OECD countries from 1975Q1 to 2022Q4. After that, this study demonstrates how this nexus behaves during high and low inflation regimes and turbulent times.

This study uses the panel autoregressive distributed lag technique to examine the nexus between housing affordability to capture the distinct characteristics of the sample countries and estimate various short- and long-run dynamics in the relationship between housing affordability and exchange rate.

Exchange rate appreciation improves housing affordability in the short run, whereas this connection tends to dissipate in the long run. Moreover, inflation can worsen housing affordability during turbulent times, such as the global financial crisis, in both the short and long run. Ignoring these changes in the relationship between exchange rates and housing affordability during turbulent times can lead to incorrect conclusions.

To the best of the authors’ knowledge, this study is the first to examine the association between exchange rates and housing affordability by demonstrating how these variables behave in high and low inflation regimes and turbulent times.