Structural Change and Economic Dynamics最新文献

This study aims to highlight the importance of accurately estimating methane emissions, one of the most dangerous and important greenhouse gases in the context of climate change. By incorporating methane emissions as a variable within the integrated assessment model DICE (Dynamic Integrated Climate-Economy model), we investigate how these emissions influence temperature changes and subsequently impact economic policies, including climate economic policies, carbon pricing, and non-price factors. We use the existing DICE-2020 and DICE-2023 models as references for our analysis. In addition to industrial emissions that can be detected through satellite observations, we address the challenge of estimating natural emissions from wetlands and permafrost, which leak gradually and are difficult to detect. By considering these emissions, we account for their exogenous nature and their divergence from the current situation. Our study reveals that incorporating methane emissions into the DICE model has significant implications for global temperature outcomes and subsequent policy changes. We find that by implementing existing methane reduction policies, which includes cutting the level of methane emissions in half and increase the carbon price in 4 times to 500 USD per ton, it is possible to achieve the more ambitious goal of limiting the global temperature increase to 1.5 °C by 2100 in an optimistic scenario instead of the common target of 2 °C. More pessimistic scenarios that do not imply big change in methane emissions, but the same numerical data for carbon price, still suggests the possibility of keeping the global temperature below 2 °C. The findings of this study emphasize the importance of estimating methane emissions in efforts to mitigate climate change. Recognizing the impact of methane on global temperature change, policymakers can make informed decisions regarding economic policies, carbon pricing, to effectively address the challenges posed by climate change. This research contributes to the field by incorporating methane emissions into the DICE model, providing a more complete understanding of its influence on global climate outcomes and economic implications. Additionally, by highlighting the potential benefits of methane reduction measures, this study provides information on how to achieve more ambitious climate targets.

Given the carbon capture and storage (CCS) technology is still in the demonstration phase, large-scale deployment of CCS is urgently needed in the coming decades, especially in the power sector. Therefore, we built a computable general equilibrium model with detailed electricity technology module and assessed the economy-wide impacts of multiple incentive policies on large-scale deployment of CCS in the power sector. Results show that, first, if only CCS is subsidized, without supplementing carbon pricing, it will lead to deviations from the core environmental objectives of CCS development. Secondly, when CCS subsidies are combined with carbon pricing, if the sectoral indirect tax is reduced, the GDP loss can be better alleviated, and it can also have an obvious positive impact on energy conservation and emission reduction. Finally, a gradual sector-coverage way of carbon pricing contributes to further mitigating the accumulated GDP loss, easing sectoral profit losses, and improving positive effects on energy indicators.

Understanding the cyclicality in aggregate productivity helps answer whether the economy allocates resources efficiently or not. The paper analyses the sources of aggregate productivity growth, such as direct efficiency gain within-plants, allocative efficiency gain, and gains due to entry and exit during economic fluctuations. In particular, we exploit the economic shock of the Great Recession to analyse the validity of the 'Cleansing’ or ‘Scarring’ effect of recession and 'Schumpeterian Darwinian Selection' for Indian manufacturing. The rise and fall of within-plant and net-entry effects during the economic fluctuations explains the pro-cyclicality of productivity growth. Plants in export-oriented industries are crucial in explaining the pro-cyclicality. Negative external shock to exporting sectors during 2008–09 shifted resources from more productive to less productive plants. The relatively productive exporters exited the markets following the global crisis, scarring the economy. Nonetheless, the positive effect from the net-entry exit of plants during the economic downturn makes the 'Schumpeterian approach of Darwinian Selection' valid.

The Goodwin–Keen model was introduced to study the structural instability of debt-financed economies. Despite its theoretical appeal, no empirical study has focused on this model to date. Using u.s. data for non-financial firms over the period 1959–2019, this paper tests the empirical validity of a Goodwin–Keen model accounting for dividends. We propose a two-step procedure to simultaneously estimate parameters and quantify their uncertainty. The model satisfactorily captures the historical cycles in the wage share and employment rate, while reflecting the trend growth in the debt-to-output ratio. The estimation provides meaningful parameters, although their large uncertainty suggests that the model fails to fully account for the private debt dynamics. The estimated model assigns a probability of at most 11% to the occurrence of a private-debt overhang over the 21st century. However, it would have failed to foretell the Global Financial Crisis. Further work is therefore needed to improve its prospective capacity.

While empirical studies exploring the impacts of international trade on income inequality have continued to expand, yielding mixed results, less attention has been devoted to the effects of BioTrade on income redistribution. This article addresses this gap by examining the impact of BioTrade on income inequality, with a specific emphasis on the role of technological innovations. We employ a panel model encompassing 131 countries over the period 2010–2019, utilizing instrumental variable two-stage least squares and smoothed instrumental-variable quantile regression. Overall, the results indicate a strong positive link between BioTrade and income inequality, yet its effects remain heterogeneous across sub-regions and the distribution of income inequality. To elucidate this positive link, the article presents evidence of the crucial role of the level of readiness for advanced technologies. Consequently, technological innovations play a pivotal role in mitigating the accelerating effects of BioTrade on inequality. The results are robust to a battery of robustness tests, including variations in estimation methodologies, alternative measures of inequality and BioTrade, and the inclusion of control variables. These results call upon policymakers to champion technological innovations, such as Internet access and research and development, as crucial strategies for effectively and sustainably alleviating the aggravation of inequalities induced by BioTrade.

The real estate sector in China has strong connections with other sectors. By employing forecast error variance decompositions from least absolute shrinkage and selection operator vector autoregression (LASSO-VAR) model, this study explores the real estate sector's role in China's sectoral network between January 1, 2000, and June 30, 2023. Our analysis reveals that the total sectoral connectedness ranged between 80% and 90% before 2016, but fluctuated between 55% and 90% from 2016 to June 2023. We also identify that shocks primarily spread from the real estate sector to the financial sector from 2014 to 2019. However, this pattern was reversed, with shocks spreading from the financial sector to the real estate sector from early 2020 to June 2023. Furthermore, we observe that the government's long-term mechanisms for the real estate sector have a significant impact on the connection between the real estate sector and the other sectors.

This paper examines the role of the circular economy and inclusive green growth in promoting energy transition and carbon neutrality for several European countries during 2009–2021, using an advanced econometric strategy. To achieve this objective, we employed a three-pronged empirical strategy. The first strategy involved standard panel specifications, such as pooled ordinary least squares, Fixed Effects, Roger panel regression, white panel regression, and Driscoll–Kraay standard errors. The second strategy explored the long- and short-term dynamics of the relationships using the dynamic specifications of the Generalised Method of Moments, comprising the augmented Arellano–Bond, Ahn–Schmidt, Arellano–Bond, and Arellano–Bover/Blundell–Bond estimators. It further controls for endoegeneity using the Two stages Lease Square (2SLS and Lewbel 2SLS). The third strategy employed the Machado and Silva quantiles via moments to re-evaluate the heterogeneity drivers of carbon neutrality. Furthermore, an alternative and complementary strategy based on the statistical procedures of Hausman–Taylor and Feasible Generalized Least Squares was employed to verify robustness. The findings suggest that prior carbon emissions positively predict future emissions. Also, our results reveal that the adoption of a circular economy, including green growth and renewable energy, can significantly contribute to reducing carbon emissions. In contrast, domestic economic drivers, and eco-innovation increase carbon emissions. We propose that policymakers mandate producers to oversee the entirety of their product life cycles as a means to mitigate carbon emissions. Furthermore, endorsing training programs and educational initiatives aimed at cultivating the requisite skills for the energy transition and the adoption of circular economy practices is imperative for ensuring the realization of a successful low-carbon economy.

In recent years, the gap between the north and the south of China has been expanding, showing a decreasing proportion of value-added and an increasing proportion of carbon emissions in the north of China, and vice versa in the south of China. Based on the most recent inter-provincial input-output table of China in 2012 and 2017, this paper focused on the North-South industrial transfer of manufacturing, quantified its impact on regional carbon emissions, and decomposed the path of impacts. The results suggest that the North-South industrial transfers of China during 2012-2017 indeed aggravated the imbalance of carbon emissions in the north and the south of China. Further explorations of path decompositions show that the spillover effect through production linkages is the major path where industrial transfer influences regional carbon emissions, particularly in the north of China. The results provide insightful policy implications for the achievement of carbon emissions reduction targets in China as well as the globe.

In this paper, we investigate the nature of path dependency in specialization of countries in terms of international trade. Our focus is on the product space density metric, which is employed in the literature on smart specialization and the product space. We find that although density is supposed to capture relatedness between a country's current specialization pattern and potential products that it may diversify into, density also contains a large component of what we call unrelated diversity, i.e., country- and product fixed effects. Together, these fixed effects capture 97 % of the variance of density. We isolate the related variety component in density and then estimate logit regressions that predict gains or losses of specialization. The relative influence of unrelated variety on changes of specialization increases with the level of diversification of the country: only countries that are not already diversified are strongly influences of related variety. We also show that the impact of the country effect in the impact of unrelated diversity in gains or keeps of specializations increases with diversity. This suggests that existing capabilities breed new capabilities, i.e., diversification is a virtuous circle that is largely independent of relatedness, and that the source of path dependency in international specialization patterns lies much more in generic production capabilities rather than relatedness in product space.

This paper assesses the intersectoral linkages of the tourism sector of the Greek economy using an extended version of the hypothetical extraction method, which allows the intersectoral effects of the labor force reproduction process to be taken into account, and data from the symmetric input-output table for the year 2015. The findings of our analysis show that the role of tourism in the Greek economy is more as a seller of inputs in other sectors than as a buyer of inputs, a finding that can be reduced to the high participation of the tourism product in the labor force reproduction process. In other words, an increase in demand for the tourism product cannot bring about a strong growth in the economy, since the sector's dependence on inputs from other sectors for its operation is low and, therefore, the increase in the tourism product does not lead to a large increase in the production of the other sectors. On the contrary, an increase in demand for the products of other sectors will lead to a strong growth of the tourism sector, since the dependence of other sectors on inputs of the tourism sector is high. The interdependencies in the production structure of the Greek economy show that the tourism sector cannot be the basis of a growth policy (i.e. by stimulating tourism demand), but, conversely, the growth of the Greek economy will lead to a significant increase in its tourism sector.