• Pro-environmental business and clean growth trends for the East Midlands 2021

      Gallotta, Bruno; Paterson, Fred; Baranova, Polina; University of Derby (University of Derby, 2021-06-01)
      Based on responses to the East Midlands Chamber (EMC) Quarterly Economic Survey (Feb 2021): • The percentage of businesses in the East Midlands deriving turnover from supplying pro-environmental goods or services increased from 16% in 2015 to 37% in 2021. • 36% of the companies surveyed stated that clean growth is already wholly or partly integrated into their business growth strategies; up from 29% in 2020. • Larger companies continue to be more advanced than smaller firms in integrating clean growth in their business strategies. • However, more than four in ten firms (42%) do not feel well informed about support for clean growth and nearly three in ten (29%) are not engaging with the clean growth agenda – a small decline from 2020. This suggests that whilst opportunity in the Low Carbon and Environmental Goods and Services (LCEGS) market is still strong, awareness and engagement with clean growth opportunities may have been weakened during the 2020/21 pandemic.
    • US partisan conflict uncertainty and oil prices

      Apergis, Nicholas; Hayat, Tasawar; Saeed, Tareq; University of Derby; King Abdulaziz, University, Saudi Arabia; Quaid-I-Azam University, Pakistan (Elsevier BV, 2021-01-13)
      This empirical study significantly contributes in building emerging literature by investigating the impact of US partisan conflict uncertainty on international oil prices. It models oil prices through non-linear Quantile Autoregressive Distributed Lag (QARDL) methods in order to consider potential (non-linear) asymmetric effects of partisan political uncertainty on oil prices. The empirical results clearly document the asymmetric (non-linear) impact of partisan conflict uncertainty on international oil prices, which has been in contrast to the linear case. The findings also expose that the transmission mechanism of partisan political uncertainty to oil prices is validated through the economic growth channel. The empirical findings contribute to existing research by assisting investors in the oil industry with risk identification, analysis, and mitigation. The results can assist in discovering the links between US political risk and oil markets, determining an important element of political risk factors facing investors who want to participate in the oil industry.
    • Another look at contagion across United States and European financial markets: Evidence from the credit default swaps markets

      Tsionas, Mike G.; Apergis, Nicholas; Lancaster University; University of Derby (Wiley, 2021-01-18)
      The paper looks at the results of Apergis, Christou and Kynigakis (2019) and proposes a novel model that allows time variation in volatility, skewness and kurtosis, based on multivariate stable distributions. The analysis also looks at bank sector CDS, insurance sector CDS, sovereign bonds, equity and volatility indices. The findings corroborate their results and indicate significant evidence of contagion, especially through the channels of co‐skewness and co‐kurtosis. In addition, it establishes a higher order channel of causality between co‐skewness and co‐kurtosis.
    • Impact of economic policy uncertainty on CO2 emissions: evidence from top ten carbon emitter countries

      Anser, Muhammad Khalid; Apergis, Nicholas; Syed, Qasim Raza; University of Architecture and Technology, Xi’an, China; University of Derby; National Tariff Commission, Ministry of Commerce, Islamabad, Pakistan (Springer Science and Business Media LLC, 2021-02-08)
      Over the last few decades, economic policy uncertainty (EPU) has surged across the globe. Furthermore, EPU affects economic activities, which may also generate strong CO2 emissions. The goal of this study is to explore the impact of EPU (measured by the world uncertainty index) on CO2 emissions in the case of the top ten carbon emitter countries, spanning the period 1990 to 2015. The findings from the PMG-ARDL modelling approach document that the world uncertainty index (WUI) affects CO2 emissions in both the short and the long run. In the short run, a 1% increase in WUI mitigates CO2 emissions by 0.11%, while a 1% rise in WUI escalates CO2 emissions by 0.12% in the long run. The findings could have some substantial practical effects on economic policies through which policy makers try to shrink any uncertainty by organizing and participating in international summits and treaties. In addition, international organizations could also launch certain programs to shrink uncertainties associated with economic policy. Finally, these countries should introduce innovation, renewable energy, and enforce alternative technologies that are environment friendly. Overall, governments must provide strong tax exemptions on the use of clean energy, while R&D budgets should also expand.
    • The causal linkage between inflation and inflation uncertainty under structural breaks: Evidence from Turkey

      Apergis, Nicholas; Bulut, Umit; Ucler, Gulbahar; Ozsahin, Serife; University of Derby; Kirsehir Ahi Evran University, Kirsehir, Turkey; Necmettin Erbakan University, Konya, Turkey (Wiley, 2021-03-03)
      The goal of this paper is to examine the relationship between inflation and inflation uncertainty for Turkey through monthly data spanning the period 2004:01–2019:12. To this end, the paper first builds the inflation uncertainty series using inflation data. Second, it examines the cointegration relationship between inflation and inflation uncertainty. Finally, it searches for causal relationships between inflation and inflation uncertainty. The paper employs econometric methods which explicitly consider structural breaks. After examining the inflation–inflation uncertainty nexus for the whole sample, the analysis also investigates this relationship in two subperiods, i.e., 2004:5–2010:10 and 2010:11:2019:12 considering the change in the monetary policy framework of the Central Bank of the Republic of Turkey (CBRT). The findings provide evidence that there exists unidirectional causality running from inflation to inflation uncertainty for both the whole sample and the second subperiod, while there is no causality between inflation and inflation uncertainty for the first subperiod. Overall, the results show that during the second subperiod (i) when the CBRT tried to achieve not only price stability, but also financial stability and (ii) when the inflation rate is more volatile and higher, the increase in the inflation rate results in an increase in inflation uncertainty.
    • Responses of carbon emissions to corruption across Chinese provinces

      Ren, Yi-Shuai; Ma, Chao-Qun; Apergis, Nicholas; Sharp, Basil; Hunan University, China; University of Auckland, New Zealand; University of Derby (Elsevier BV, 2021-03-19)
      In response to the recent growth of multitudes of theoretical literature analysing the corruption impact on the economy and environment, this paper subjects the corruption–carbon emission relationship in China to a detailed empirical examination through the autoregressive distributed lag modelling approach and panel quantile regressions. Based on panel data from Chinese provinces, spanning the period 1998–2016, this study explores the impact of long- and short-term corruption on per capita carbon emissions by considering the heterogeneous distribution of those emissions. The results document that corruption increases per capita carbon emissions in Chinese provinces in the short run, reducing per capita carbon emissions in the long run. Moreover, an increase in corruption leads to an increase in carbon emissions per capita in all quantiles, indicating that these emissions increase with corruption severity. The coefficients in low quantiles are slightly larger than those in high quantiles, indicating that corruption leads to more carbon emissions in provinces with lower per capita carbon emissions.
    • The asymmetric relationship of oil prices and production on drilling rig trajectory

      Apergis, Nicholas; Ewing, Bradley T.; Payne, James E.; University of Derby; Texas Tech University, Lubbock, TX, USA; The University of Texas at El Paso, El Paso, TX, USA (Elsevier BV, 2021-01-22)
      With active drilling rigs essential for replenishing oil resources depleted through production, this study examines the potential asymmetries between drilling rig trajectory (vertical, directional, and horizontal), oil prices and oil production in the U.S. within a nonlinear autoregressive distributed lag framework. Based on weekly data, the results reveal long-run symmetry with respect to oil prices irrespective of drilling rig trajectory. However, there is long-run asymmetry for oil production consistent with the capital-intensive nature of drilling and the fixed costs associated with new wells. The results also show short-run asymmetry with respect to both oil prices and oil production consistent with companies taking advantage of upturns quickly and refraining from costly shut-in, plug and abandon, or increased expenditures on improved oil recovery during downturns.
    • The role of macroeconomic and geopolitical news on gold returns and volatility

      Apergis, Nicholas; Hayat, Tasawar; Saeed, Tareq; University of Derby; King Abdulaziz University (Oviedo University Press, 2021-02-21)
      The goal of this paper is to explore the simultaneous role of macroeconomic and geopolitical news in gold returns and its associated volatility. The analysis uses sentiment scores for certain macroeconomic and geopolitical global news, along with a GARCH modelling approach. The findings document that both types of news substantially impact gold returns and their associated volatility, with geopolitical news having a stronger impact.
    • 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.