• Forecasting US overseas travelling with univariate and multivariate models

      Apergis, Nicholas; University of Derby (Wiley, 2021-01-06)
      This study makes use of specific econometric modelling methodologies to forecast US outbound travelling flows to certain destinations: Europe, Caribbean, Asia, Central America, South America, Middle East, Oceania, and Africa, spanning the period 2000-2019 on a monthly basis. Both univariate (jointly with business conditions) and multivariate models are employed, while out-of-sample forecasts are generated and the results are compared based on popular forecasting performance criteria. These criteria show that in the case of univariate models, the largest forecasting gains are obtained when the modelling process follows the KS-AR(1) model with the business cycles being measured as the coincident indicator. In the case of multivariate models, the largest forecasting gains occur with the standard VAR model for very short forecasting horizons, and with the Bayesian VAR for longer horizons. The results are robust to both total and individual destinations. The findings allow interested stakeholders to gain insights into near-future US outbound tourism to popular diversified international destinations, as well as to better understand its positive and negative impacts for strategic planning and destination adaptation purposes.
    • The impact of economic freedom on the gender pay gap: evidence from a survey of UK households

      Apergis, Nicholas; Lynch, Nicola; University of Derby (Emerald, 2020-12-25)
      Purpose-Using survey datasets, this work explores the impact of economic freedom on the gender pay gap. Design/methodology/approach-The analysis combines Economic Freedom of the World data with the Understanding Society (USoc) Microdata series to determine the association between economic freedom, and its respective components, and the gap in pay between males and females in the U.K. Findings-The results document that economic freedom positively affects the gender pay gap. When the components of the index are considered, the findings indicate different effects of various types of policy, i.e. less government spending, stronger trade liberalization conditions and levels of corruption lead to higher gaps; stronger legal and property rights and a sounder money system have no impact on the gap. Moreover, a stronger impact in the manufacturing industry, part-time workers and those who work in the non-London regions is observed. The results survived certain robustness tests. Practical implications-The findings imply that reductions to government spending programmes can potentially aggravate the gap in hourly wages paid between males and females and should, therefore, be implemented. It may be also possible to provide females the training or education necessary to effectively compete in the workforce, before eliminating any spending programme they rely on.
    • The influence of economic policy uncertainty and geopolitical risk on U.S. citizens overseas air passenger travel by regional destination

      Apergis, Nicholas; Payne, James; University of Derby; University of Texas at El Paso (SAGE, 2020-12-22)
      This research note extends the literature on the role of economic policy uncertainty and geopolitical risk on U.S. citizens overseas air travel through the examination of the forecast error variance decomposition of total overseas air travel and by regional destination. Our empirical findings indicate that across regional destinations U.S. economic policy uncertainty explains more of the forecast error variance of U.S. overseas air travel followed by geopolitical risk with global economic policy uncertainty explaining a much smaller percentage of the forecast error variance.
    • Florida metropolitan housing markets: examining club convergence and geographical market segmentation

      Apergis, Nicholas; Payne, James; University of Derby; University of Texas at El Paso (Taylor and Francis, 2020-06-10)
      This study explores the convergence of housing prices for 21 metropolitan areas within the state of Florida for the quarterly period 1987:2 to 2017:3. The examination of house price differentials between metropolitan and state-level house prices using a battery of univariate and panel unit root testing approaches yielded mixed results with respect to the presence of convergence. However, the Phillips-Sul (2007; 2009) club convergence approach identifies four distinct convergence clubs for metropolitan area house prices within Florida with a relatively clear geographical segmentation of the housing market.
    • Evaluating tail risks for the US economic policy uncertainty

      Apergis, Nicholas; University of Derby (Wiley, 2020-12-03)
      The goal of this paper is to employ a relatively new methodological approach to extract quantile-based economic policy uncertainty risk forecasts using the Quantile Autoregressive Distributed Lag Mixed-Frequency Data Sampling (QADL-MIDAS) regression model recommended by Ghysels and Iania (2018). This type of modelling delivers better quantile forecasts at various forecasting horizons. The forecasting results not only imply that the risk measure of economic policy uncertainty measure is linked to the future evolution of the index itself, but also it help constructing explicitly EPU risk measures, which are used to identify what drives such risk policy measures, especially across certain sub-sample periods associated with major global events, such as the collapse of the Lehman Brothers, the Trump’s election, and the trade-war tensions between the US and China. The findings offer a new empirical perspective to the existing economic policy uncertainty literature, documenting that special world events carry a strong informational content as being a primary key to understand the dynamics of the economic policy tails.
    • Cyclicality of commodity markets with respect to us economic policy uncertainty based on granger causality in quantiles

      Apergis, Nicholas; Hayat, Tasawar; Saeed, Tareq; University of Derby; King Abdulaziz University (Wiley, 2020-10-21)
      Given the importance of U.S. in global commodity markets, the goal is to explore whether US economic policy uncertainty impacts the price performance of certain commodities. The analysis uses the Granger causality in quantiles method that allows us to test whether there are different effects under different market conditions. The results document that economic uncertainty impacts the returns on the commodities considered, with the effects clustering around the tail of their conditional distribution. Robust evidence was obtained under alternative definitions of uncertainty.
    • Fracking and asset prices: The role of health indicators for house prices across Oklahoma’s counties

      Apergis, Nicholas; Ghosh Dastidar, Sayantan; Mustafa, Ghulam; University of Derby (Springer, 2020-11-27)
      The paper extends Apergis’s (2019) study on the role of fracking activities in housing prices across Oklahoma countries by explicitly considering the role of certain indicators determining the health profile of the population. The analysis employs a panel model approach using data from 76 Oklahoma counties, spanning the period 1996-2015. The findings clearly indicate that the overall impact of fracking on housing prices is negative, given that the health indicators are explicitly considered, i.e. fracking has lowered housing prices.
    • A novel hybrid approach to forecast crude oil futures using intraday data

      Apergis, Nicholas; Manickavasagam, Jeevananthan; Visalakshmi, S.; University of Derby; International Management Institute; Central University of Tamil Nadu (Elsevier, 2020-06-04)
      Prediction of oil prices is an implausible task due to the multifaceted nature of oil markets. This study presents two novel hybrid models to forecast WTI and Brent crude oil prices using combinations of machine learning and nature inspired algorithms. The first approach, MARSplines-IPSO-BPNN, Multivariate Adaptive Regression Splines (MARSPlines) find the important variables that affect crude oil prices. Then, the selected variables are fed into an Improved Particle Swarm Optimization (IPSO) method to obtain the best estimates of the parameters of the Backpropagation Neural Network (BPNN). Once these parameters are obtained, the variables are fed into the BPNN model to generate the required forecasts. The second approach, MARSplines-FPA-BPNN, generates the parameters of BPNN through the Flower Pollination Algorithm (FPA). The forecasting performance of these new models is compared to certain benchmark models. The findings document that the MARSplines-FPA-BPNN model performs better than the other competitive models.
    • Do global sentiment shocks spillover towards emerging and frontier markets?

      Apergis, Nicholas; Rehman, Mobeen; University of Derby; Ton Duc Thang University (Emerald, 2020-02-28)
      This study aims to investigate the impact of sentiment shocks based on US investor sentiments, bearish and bullish market conditions. Earlier studies, though very few, only consider the effect of investor sentiments on stock returns of emerging frontier Asian (EFA) markets. This study uses the application of regime switching model because of its capability to explore time-varying causality across different regimes unlike traditional linear models. The Markov regime switching model uses regime switching probabilities for capturing the potential asymmetries or non-linearity in a model, in this study’s case, thereby adjusting investor sentiments shocks to stock market returns. The results of the Markov regime switching method suggests that US sentiment, bullish and bearish market shocks act as a main contributors for inducing variation in EFA stock market returns. The study’s non-parametric robustness results highlight an asymmetric relationship across the mean series, whereas a symmetric relationship across variance series. The study also reports Thailand as the most sensitive market to global sentiment shocks. The sensitivity of the EFA markets to these global sentiment shocks highlights their sensitivity and implications for investors relying merely on returns correlation and spillover. These findings also suggest that spillover from developed to emerging and frontier equity markets only in the form of returns following traditional linear models may not be appropriate. This paper supports the behavioral aspect of investors and resultant spillover from developed market sentiments to emerging and frontier market returns across international equity markets offering more rational justification for an irrational behavior. The study’s motivation to use the application of regime switching models is because of its capability to explore time-varying causality across different regimes unlike traditional linear models. The Markov regime switching model uses regime switching probabilities for capturing the potential asymmetries or non-linearity in a model, in the study’s case, thereby adjusting investor sentiments shocks to stock market returns. It is also useful of the adjustment attributable to exogenous events.
    • How do human rights violations affect poverty and income distribution?

      Apergis, Nicholas; Cooray, Arusha; University of Derby; Embassy of Sri Lanka in Oslo, Norway (Elsevier BV, 2019-11-13)
      Employing data for 125 countries and spanning the 1990–2014 period, we empirically examine the impact of human rights on income distribution and poverty. We also investigate how aid and trade can influence poverty and income distribution through human rights. The results suggest that stronger human rights records contribute to greater income equality, as well as to poverty reduction. The interaction of human rights with both ODA and trade show that as aid and trade flows increase, or alternatively as human rights records increase, ODA and trade flows reduce poverty and lead to greater equality in income distribution.
    • Corruption, rentier states and economic growth: Where do the GCC Countries stand?

      Apergis, Nicholas; Ali, Mohamed Sami Ben; University of Derby; Qatar University (Springer, 2020-10-27)
      Countries with vast natural resources usually display low economic outcomes and corruption is always considered as a main economic hinderer in this regard. We consider in this study the Gulf Cooperation Countries as endowed with huge natural resources while considering the potential role of corruption on their economic growth. We first theoretically discuss both the cursing and the blessing effect of natural resources on countries’ economic outcomes. The empirical analysis employed the panel GMM approach to explore whether and how the investment channel and the political stability channel can contribute to explaining the link between corruption and economic growth. Estimation outcomes show that overall corruption negatively impacts economic growth. Given that usually, corruption occurs through the interaction of the business with the public sector, regulatory authorities, as well as policymakers should spend their efforts to improve the transparency of communication between firms and public entities and officials. The result is expected to reduce their discretionary power, as well as the expected gains from corruption. Overall, these countries need to adopt certain institutional reforms, leading to higher accountability, the strength of property rights, and better bureaucratic quality.
    • Asymmetric effects of inflation instability and GDP growth volatility on environmental quality in Pakistan

      Apergis, Nicholas; Ullah, Sana; Usman, Ahmed; Chishti, Muhammad Zubair; University of Derby; Quaid-i-Azam University; Government College University Faisalabad; Quaid-i-Azam University (Springer, 2020-06-06)
      This study inspects the empirical association between inflation instability, GDP growth volatility, and the environmental quality in Pakistan, covering the period 1975-2018 by using an asymmetric autoregressive distributed lag (ARDL) methodological approach. The asymmetric ARDL results document that positive and negative shocks of inflation instability have different effects on environmental quality. Negative shocks of inflation instability have a positive influence on carbon dioxide emissions (CO2) and nitrous oxide emissions (N2O), while positive shocks of inflation instability have insignificant effects in the long run. Asymmetric findings also suggest that positive and negative fluctuations in GDP growth volatility affect CO2 and N2O emissions differently, while they have insignificant results on methane emissions (CH4) in the long run. Additionally, in the short-run, positive and negative shocks of inflation instability and GDP growth volatility behave differently in terms of their impact on pollution emissions. Based on these findings, the study opens up innovative intuitions for policymakers to support a robust role of economic stability in attaining targets relevant to pollution reduction.
    • Industry momentum and reversals in stock markets

      Apergis, Nicholas; Plakandaras, Vasilios; Pragidis, Ioannis; University of Derby; Democritus University of Thrace (Wiley, 2020-10-19)
      Although price trends such as momentum and reversal patterns of stock prices are well established in the literature, little is known whether price patterns still hold at the international level. Using data from over 24,000 stock prices, the analysis forms international within and across industries portfolios for the EU and the Asia/Pacific regions and studies the presence of momentum and reversal patterns, compared with the typical benchmark, which is the U.S. market. Interestingly, it finds that both patterns are related to low capitalized firms. Price reversals appearing only at the short-run validating the liquidity constraint assumption, while momentum holds for a longer period and is related to investors’ underreaction. Finally, it finds that only a few sectors can predict the market as an indirect result of momentum. A trading strategy that builds on industries’ portfolios own predictive ability beats the market. Overall, matching returns patterns from the national to the international level supports the presence of unobserved risk factors and behavioral biases.
    • The impacts of R&D investment and stock markets on clean energy uses and CO2 emissions in a panel of OECD economies

      Apergis, Nicholas; Alam, Md. Samsul; Paramati, Sudharshan Reddy; Fang, Jianchun; University of Derby; De Montfort University; University of Dundee; Zhejiang University of Technology (Wiley, 2020-09-14)
      The goal of this paper is to examine to what extent R&D investment and stock market development promote clean energy consumption and environmental protection across a panel of 30 OECD economies. Based on the IPAT theoretical approach, study employs robust panel econometric models which account for cross-sectional dependence in the analysis and uses annual data, spanning the period 1996 to 2013. The empirical results illustrate that R&D and stock market have a significant long-run equilibrium relationship with clean energy and CO2 emissions. The long-run elasticities display that R&D and stock market growth have a significant positive impact on clean energy consumption, while they have a negative effect on the growth of CO2 emissions. Given these findings, the paper suggests that the policy makers in the OECD economies should realize that it is worth investing in R&D activities as it is promoting the use of clean energy and ensuring low carbon economies. Therefore, the policymakers have to initiate effective policies to promote R&D activities and also encourage the firms that are listed in the stock market to adopt environmental friendly policies.
    • Natural disasters and housing prices: Fresh evidence from a global country sample

      Apergis, Nicholas; University of Derby (Asian Real Estate Society, 2020)
      Given that the literature on the impact of natural disasters on house prices is highly limited, this paper combines data on natural disasters and house prices from 117 countries, spanning the period 2000-2018 and a panel regression method to estimate the effects of natural disasters on house prices. The findings document that natural disasters lead to lower house prices, with the results surviving a number of robustness tests. When examining the impacts of natural disasters by type, the findings highlight that geological disasters exert the strongest (negative) impact on house prices. The results also illustrate the negative impact of those disasters on house prices when the distinction between small and large disasters is also accounted. The findings provide important implications for policymakers and property investors. Lower house prices in countries experience natural disasters events could significantly signify lower consumption and investment (the wealth effect), with further negative spillovers to the real economy. Economic policymakers could implement low-tax policies or quantitative easing schemes to support these areas/countries. The findings exemplify the need of governments and policymakers to mitigate climate change effects on housing by adopting new, more environmentally friendly technologies and energy sources.
    • Pro-environmental business and clean growth trends for the East Midlands 2020

      Paterson, Fred; Baranova, Polina; Gallotta, Bruno; University of Derby (University of Derby, 2020-06-01)
      Based on responses to the East Midlands Chamber (EMC) Quarterly Economic Survey (Feb 2020): The percentage of businesses in the East Midlands deriving turnover from low carbon and pro-environmental goods and services has nearly doubled between 2015 and 2020: increasing from 16% in 2015 to 31% in 2020. 36% of businesses say their environmental strategy is strongly linked with their business growth strategy. However, four in ten firms do not feel well informed about support for clean growth and more than a quarter (26%) are not engaging with the clean growth agenda.
    • Investigating the impact of auto loans on unemployment: The US experience

      Apergis, Emmanuel; Apergis, Nicholas; Young, Weiwei; University of Derby; University of Huddersfield (Taylor & Francis, 2020-07-28)
      This paper explores the impact of automobile loan debt on US unemployment. Individuals with heterogeneous economic positions deem automobiles as important durable goods for unemployment exit and expected wage increases. The methodological approach makes use of an Autoregressive Distributed Lag (ARDL) Bound Testing modelling approach to document a negative and significant relationship between auto loans and unemployment. The results survive certain robustness tests, while they seem to confirm certain theoretical arguments posed in the literature, such as that the credit mechanism that dominates the transmission mechanism of monetary policy (credit shocks have a profound significant link with unemployment), while they seem to mitigate the role of alternative theories (where levered households suffer from a ‘debt overhang’ problem that distorts their preferences, making them demand high wages, and the ‘vacancy-posting’ effect) which imply that loans lead to high unemployment. The findings seem to provide significant recommendations to monetary policy makers on strengthening the banking services industry, providing an alternative to monetary policy for labour market intervention.
    • Convergence in cryptocurrency prices? The role of market microstructure

      Apergis, Nicholas; Koutmos, Dimitrios; Payne, James; University of Derby; Worcester Polytechnic Institute; University of Texas, El Paso (Elsevier, 2020-07-04)
      Do we observe convergence between cryptocurrencies over time? This study explores this question with eight major cryptocurrencies in circulation and posits a framework to evaluate whether shifts in their market microstructures drive convergence. Three main findings emerge. First, convergence can emerge between cryptocurrencies with distinct technological functions and classifications. Second, market microstructure behavior drives convergence. Third, estimated transition paths show tighter convergence for half of our sampled cryptocurrencies during the time when the Chicago Board of Exchange (CBOE) introduced bitcoin futures contracts.
    • Dependence structure in the Australian electricity markets: New evidence from regular vine copulae

      Apergis, Nicholas; Gozgor, Giray; Lau, Chi Keung; Wang, Shixuan; University of Derby; Istanbul Medeniyet University; University of Huddersfield; University of Reading (Elsevier, 2020-07-01)
      In this study, regular vine copula was used to investigate the dependence structure of electricity prices at the state level in the Australian National Electricity Market (NEM), during three periods related to the adoption and abolition of the carbon tax. In the pre-carbon period, we found evidence of tail dependence separately in the northern and southern NEM, but not across them. During the carbon period, the joint spike in the northern NEM disappeared, and the tail dependence in the southern NEM decreased. In the post-carbon period, the best dependence structure turned out to be a flexible structure of the regular vine, which exactly matches the geographical infrastructure connectedness of transmission wires. Besides, both upper and lower tail dependences were found in all adjacent states after the abolition of the carbon tax, suggesting a more integrated market regarding tail dependence. Our findings have substantial implications for risk management in the NEM, especially for those participants exposed to multiple states.
    • Greenhouse gas emissions convergence in Spain: Evidence from the club clustering approach

      Apergis, Nicholas; Garzón, Antonio; University of Derby; University of Seville (Springer, 2020-07-05)
      This study examines the convergence of greenhouse gas emissions per capita across the 19 Spanish regions using the Phillips-Sul club convergence approach over the period spanning from 1990 to 2017. The results indicate the existence of 3 clubs which converge to different equilibria and correspond to the same convergence clubs in terms of income per capita. These findings suggest that mitigation policies should take into account the existence of different clubs of regions with different convergence paths in terms of emissions.