Testing Wagner’s law versus the Keynesian hypothesis for GCC countries

© 2020 Informa UK Limited, trading as Taylor & Francis Group. This paper examines the relationship between real GDP and government spending for the six Gulf Cooperation Council (GCC) countries. Linear Granger causality tests in the time and frequency domains provide moderate support for Wagner’s law in four countries and weak support for the Keynesian model in two countries. In contrast, asymmetric nonlinear causality tests in the frequency domain support Wagner’s law in five countries, while some form of the Keynesian hypothesis is valid in all six GCC countries. Our results illustrate the importance of using nonlinear, asymmetric models to examine causal relationships

Nature and Climate Change Effects on Economic Growth: An LSTM Experiment on Renewable Energy Resources

Global energy demand increases overtime, especially in emerging market economies, producing potential negative environmental impacts, particularly on the long term, on nature and climate changes. Promoting renewables is a robust policy action in world energy-based economies. This study examines if an increase in renewables production has a positive effect on the Brazilian economy, partially offsetting the SARS-CoV2 outbreak recession. Using data on Brazilian economy, we test the contribution of renewables on the economy via a ML architecture (through a LSTM model). Empirical findings show that an ever-greater use of renewables may sustain the economic growth recovery, generating a better performing GDP acceleration vs. other energy variables

Examining the role of digitalization and technological innovation in promoting sustainable natural resource exploitation

In the era of technological advancement, the potential of digitalization and technical innovation to revolutionize sustainable resource exploitation has become a focal point. The promises of reduced environmental impact, heightened efficiency, and improved socio-economic outcomes underscore the transformative power that digitalization holds for resource management. To this extent, the fuzzy Analytical Hierarchy Process (AHP) and fuzzy VIsekriterijumsko KOmpromisno Rangiranje (VIKOR) methods are used to examine challenges and come up with possible solutions for the mining sector in Pakistan to adopt digital transformation. The study identifies several key challenges, sub-challenges, and strategies, giving readers a thorough grasp of digital transformation. These challenges and sub-challenges are evaluated and ranked according to their relative weights using the fuzzy AHP approach. The fuzzy VIKOR method is applied to determine strategies that can help overcome these challenges and promote digitalization and technological innovation in the sustainable exploitation of natural resources. The results of fuzzy AHP show that policy and regulation, infrastructure, and human capital are key challenges. The findings of fuzzy VIKOR indicate that robust policy development, investment in Research and Development (R&D), and leveraging global trends and partnerships are key strategies to overcome the challenges. These findings provide valuable insights for policymakers, researchers, and practitioners, offering new perspectives on integrating digital technology into the natural resource sector to foster sustainable development

Heterogeneous effects of temperature and emissions on economic productivity across climate regimes

© 2021 The Authors The impact of climate change has resulted in several long-term events including extreme temperatures. Besides, the occurrence of climate events impedes economic progress––affecting economic readiness of climate mitigation. However, the effect of climatic factors on economic productivity has not been extensively covered in existing literature, especially among climate regimes. Here, we use sophisticated panel and time series techniques to examine the heterogeneous effects of temperature and emissions on income from 1960 to 2014. Our empirical results indicate a 1% rise in temperature declines income by 0.39% whereas 1% increase in emission levels stimulates income by 0.22%. This implies a mutual relationship between income and emissions––where environmental pollution supports wealth creation and vice versa. We find that a shift from optimal temperature levels to extreme patterns hamper economic productivity. Extreme temperatures affect heating and cooling degree days due to increased energy requirements, hence, escalating energy demand and emissions. With the agenda towards emission reduction, this study emphasizes economic structural change through transition from brown to green growth

Electricity demand, GDP and employment: evidence from Italy

This paper applies time series methodologies to examine the causal relationship among electricity demand, real per capita GDP and total labor force for Italy from 1970 to 2009. After a brief introduction, a survey of the economic literature on this issue is reported, before discussing the data and introducing the econometric techniques used. The results of estimation indicate that one cointegrating relationship exists among these variables. This equilibrium relation implies that, in the long-run, GDP and labor force are correlated negatively, as well as GDP and electricity. Moreover, there is a bi-directional Granger causality flow between real per capita GDP and electricity demand; while labor force does not Grangercause neither real per capita GDP nor electricity demand. This implies that electricity demand and economic growth are jointly determined at the same time for the Italian case. The forecast error variance decomposition shows that forecast errors in real per capita GDP are mainly caused by the uncertainty in GDP itself, while forecast errors in labor force are mainly resulted from the labor force itself, although aggregate income and electricity are important, too

Disaggregated Public Spending, GDP and Money Supply: Evidence for Italy

The aim of this article is to analyze the relationship between public spending and GDP controlling for the money supply in Italy for the period 1990-2010 at a disaggregated level, using a time series approach. After a brief introduction, a survey of the economic literature on this issue is shown, before estimating this nexus for ten items of public spending according to the COFOG functional classification. Cointegration tests reveal a long-run relationship between GDP, money supply and eight spending items. Moreover, Granger causality tests results show evidence in favour of Wagner’s Law in two cases (YG), while a bi-directional flow has been found in only one case. The Keynesian hypothesis (GY) is supported by five series of spending. Some notes on the policy implications of this analysis conclude the paper

Wagner's Law in Italy, Empirical Evidence from 1960 to 2008

“Wagner’s Law” is the first model of public expenditure in the history of public finance. The aim of this article is to assess its empirical evidence in Italy for the period 1960-2008. After a brief introduction, an essential survey of the economic literature on this issue is offered, before evaluating the specifications of “Wagner’s Law” due either to Ram or Koop & Poirier. Wagner’s original specification is also evaluated. A few notes on the expenditure policy in Italy conclude the paper

‘Legge di Wagner’ e spesa pubblica disaggregata: un approccio VAR

Wagner’s Law is the first model of public expenditure in the history of public finance. The aim of this article is to assess its empirical evidence in Italy for the period 1960-2008 at a disaggregate level, with a var approach. After a brief introduction and a survey of the economic literature on this issue the specifications of Wagner’s Law for some specific public expenditures are estimated. Wagner’s original specification is also estimated. Some notes on the long-term relation between public spending and national income conclude the paper