International R&D Spillovers and other Unobserved Common Spillovers and Shocks

Studies which are based on Coe and Helpman (1995) and use weighted foreign R&D variables to estimate channel-specific R&D spillovers disregard the interaction between international R&D spillovers and other unobserved common spillovers and shocks. Using a panel of 50 economies from 1970-2011, we find that disregarding this interaction leads to inconsistent estimates whenever knowledge spillovers and other unobserved effects are correlated with foreign and domestic R&D. When this interaction is modeled, estimates are consistent; however, they confound foreign and domestic R&D effects with unobserved effects. Thus, the coefficient of a weighted foreign R&D variable cannot capture genuine channel-specific R&D spillovers.Comment: 28 page

Oil, Volatility and Institutions:Cross-Country Evidence from Major Oil Producers

This paper examines the long-run effects of oil revenue and its volatility on economic growth as well as the role of institutions in this relationship. We collect annual and monthly data on a sample of 17 major oil producers over the period 1961. 2013, and use the standard panel autoregressive distributed lag (ARDL) approach as well as its cross-sectionally augmented version (CS-ARDL) for estimation. Therefore, in contrast to the earlier literature on the resource curse, we take into account all three key features of the panel: dynamics, heterogeneity and cross-sectional dependence. Our results suggest that (i) there is a significant negative effect of oil revenue volatility on output growth, (ii) higher growth rate of oil revenue significantly raises economic growth, and (iii) better fiscal policy (institutions) can offset some of the negative effects of oil revenue volatility. We therefore argue that volatility in oil revenues combined with poor governmental responses to this volatility drives the resource curse paradox, not the abundance of oil revenues as such

Long-Run Effects in Large Heterogenous Panel Data Models with Cross-Sectionally Correlated Errors

This paper develops a cross-sectionally augmented distributed lag (CS-DL) approach to the estimation of long-run effects in large dynamic heterogeneous panel data models with cross-sectionally dependent errors. The asymptotic distribution of the CS-DL estimator is derived under coefficient heterogeneity in the case where the time dimension (T) and the cross-section dimension (N) are both large. The CS-DL approach is compared with more standard panel data estimators that are based on autoregressive distributed lag (ARDL) specifications. It is shown that unlike the ARDL type estimator, the CS-DL estimator is robust to misspecification of dynamics and error serial correlation. The theoretical results are illustrated with small sample evidence obtained by means of Monte Carlo simulations, which suggest that the performance of the CS-DL approach is often superior to the alternative panel ARDL estimates particularly when T is not too large and lies in the range of 30 _ T < 100

Oil, Volatility and Institutions:Cross-Country Evidence from Major Oil Producers

This paper examines the long-run effects of oil revenue and its volatility on economic growth as well as the role of institutions in this relationship. We collect annual and monthly data on a sample of 17 major oil producers over the period 1961. 2013, and use the standard panel autoregressive distributed lag (ARDL) approach as well as its cross-sectionally augmented version (CS-ARDL) for estimation. Therefore, in contrast to the earlier literature on the resource curse, we take into account all three key features of the panel: dynamics, heterogeneity and cross-sectional dependence. Our results suggest that (i) there is a significant negative effect of oil revenue volatility on output growth, (ii) higher growth rate of oil revenue significantly raises economic growth, and (iii) better fiscal policy (institutions) can offset some of the negative effects of oil revenue volatility. We therefore argue that volatility in oil revenues combined with poor governmental responses to this volatility drives the resource curse paradox, not the abundance of oil revenues as such

Debt, Inflation and Growth: Robust Estimation of Long-Run Effects in Dynamic Panel Data Models

This paper investigates the long-run effects of public debt and inflation on economic growth. Our contribution is both theoretical and empirical. On the theoretical side, we develop a cross-sectionally augmented distributed lag (CS-DL) approach to the estimation of long-run effects in dynamic heterogeneous panel data models with cross-sectionally dependent errors. The relative merits of the CS-DL approach and other existing approaches in the literature are discussed and illustrated with small sample evidence obtained by means of Monte Carlo simulations. On the empirical side, using data on a sample of 40 countries over the 1965-2010 period, we find significant negative long-run effects of public debt and inflation on growth. Our results indicate that, if the debt to GDP ratio is raised and this increase turns out to be permanent, then it will have negative effects on economic growth in the long run. But if the increase is temporary, then there are no long-run growth effects so long as debt to GDP is brought back to its normal level. We do not find a universally applicable threshold effect in the relationship between public debt and growth. We only find statistically significant threshold effects in the case of countries with rising debt to GDP ratios

Is There a Debt-threshold Effect on Output Growth?

This paper studies the long-run impact of public debt expansion on economic growth and investigates whether the debt-growth relation varies with the level of indebtedness. Our contribution is both theoretical and empirical. On the theoretical side, we develop tests for threshold effects in the context of dynamic heterogeneous panel data models with cross-sectionally dependent errors and illustrate, by means of Monte Carlo experiments, that they perform well in small samples. On the empirical side, using data on a sample of 40 countries (grouped into advanced and developing) over the 1965-2010 period, we and no evidence for a universally applicable threshold effect in the relationship between public debt and economic growth, once we account for the impact of global factors and their spillover effects. Regardless of the threshold, however, we find significant negative long-run effects of public debt build-up on output growth. Provided that public debt is on a downward trajectory, a country with a high level of debt can grow just as fast as its peers

Assessing the relevance of the Granger non-causality test for energy policymaking:theoretical and empirical insights

This paper highlights the relevance of Granger non-causality tests in energy economics research, particularly for informing public policy decisions. While approaches such as CS-ARDL and estimators like AMG and CCEMG are widely used, they do not fully capture the predictive relationships between variables. To illustrate this, we revisit the findings of Irfan et al. (2023), who analyzed factors influencing energy transitions in G-7 and E−7 economies using Westerlund's (2007) cointegration method and CS-ARDL. Additionally, we incorporate data from Zhao et al. (2024) to estimate the relationships between artificial intelligence, GDP, trade, population, and energy efficiency using the CS-ARDL approach, complemented by Granger non-causality tests. Our results, in some cases, expand upon the evidence provided by Irfan et al. (2023), while in others, they suggest a different interpretation of key relationships. Specifically, we find that the mineral market does not exhibit significant predictive power over energy transition, whereas trade and economic growth contribute meaningfully to renewable energy development. Furthermore, using data from Zhao et al. (2024), we confirm that incorporating non-causality tests enhances the interpretation of CS-ARDL estimates, demonstrating that these tests provide valuable insights into the directionality of economic and energy relationships, which is important for policy formulation. These findings highlight the importance of integrating non-causality tests with traditional econometric methods to derive more robust and policy-relevant conclusions.</p

Impact of nuclear and renewable energy on CO2 emissions in OECD countries under the STIRPAT model: Evidence from the CS-ARDL model

In-depth evaluations of the short- and long-term effects of nuclear and renewable energy on emissions of carbon dioxide in 12 OECD countries are made in this study using the STIRPAT model. Using yearly data for the years 1980 to 2020, the CIPS unit root test, taking into account cross-sectional dependency (CD), Gengenbach et al. (2016) co-integration test, and Cross-Sectional Augmented Autoregressive Distributed Lag (CS-ARDL) technique are used. Additionally, the Dumitrescu-Hurlin (DH) panel causality tests are used for seeking&nbsp;the causal connections between variables. The empirical findings from the CS-ARDL approach demonstrate that CO2 emissions are negatively impacted both in the short and long terms by nuclear and renewable energy. The CS-ARDL results also show that the long-run elasticity of economic growth is lower than the short-run elasticity, and that growing populations increases CO2 emissions both in the short and long runs. According to the DH panel's findings on causality, there is only one way that economic development, CO2 emissions, and nuclear energy output are related. These findings suggest that the OECD should concentrate on income-oriented policies, promote green economic growth, and subsidize greater nuclear and renewable energy consumption through

Evidence For A Ladder Of Investment In Central And Eastern European Countries

The model of liberalisation of European telecommunications markets had followed what has become known as the “ladder of investment” (LoI) hypothesis: under this hypothesis entrants are expected to make progressively greater investments in their own networks, whilst decreasing their dependence on the network of the incumbent fixed operator. The ultimate goal of the LoI approach is to achieve, where feasible, inter-platform competition. From a theoretical perspective, there are opposing forces at work: whilst offering retail services based on access to the incumbent’s network at the ‘first rung’ of the ladder is less risky, access seekers may find that investing to step-up on the ‘second and higher rungs’ of the ladder too risky. It is therefore unclear from a theoretical perspective whether the LoI approach will lead to inter-platform competition. Whether and under what circumstances it would is thus an empirical question. Our paper focuses on the evidence for the LoI in Central and Eastern European (CEE) countries. Our analysis shows that the evidence available for CEE is consistent with entrants in CEE countries largely by-passing the LoI, by directly investing in their own networks. There are good reasons for this, as some of the assumptions underlying the LoI theory, such as good quality and universally available copper networks and relatively high cost and risk of investing in alternative infrastructure, do not necessarily hold in CEE countries. Our paper’s results are broadly consistent with most of the existing literature and represents a valuable contribution by providing an insight into the applicability of the LoI to CEE countries

Ecological innovation for environmental sustainability and human capital development: the role of environmental regulations and renewable energy in advanced economies

This study examines the trends in environmental sustainability and human well-being through green technologies, clean energy, and environmental taxes using panel data for the top eight advanced economies from 1990 to 2018. The study applies an advanced panel technique, cross-sectionally augmented distributed lags (CS-ARDL), to find long-run and short-run associations between these variables. Moreover, the role of foreign investment is added as a control variable. The CS-ARDL estimation confirms the productive impact of green technologies on environmental and human well-being, providing that it helps to reduce haze pollution while promoting human development. Moreover, clean energy and environmental taxes contribute toa sustainable environment and human development. Moreover, foreign investment is a direct source of haze pollution because of more industrialization and economic activities. The study finally recommends strengthening the promotion of green technology and clean energy to achieve both environmental and human well-being in the long run