Global Industrial Development: Insights From the Distribution Dynamics Approach for the Post Covid Era

The spread of COVID-19 has significantly dampened global economic activity and has also wreaked havoc on the industrial sector. Understanding the disparity and convergence of global industrial outputs is important in assessing the effectiveness of concurrent development policies. This study investigates the spatial distribution of global industrial output to unveil the disparity in industrial development and the feasibility of achieving convergence over time. Stochastic kernel analyses are carried out for national regimes to study the overall pattern of industrialization for all the countries in the world. Countries are then classified into different groups to further analyse the geographical and income effects on industrial development. The results show that disparity between the Global North and the Global South will enlarge further in the future. Industrial development in the Global North will continue to prosper, while the industrial output in many countries in the Global South just cannot reach the global average.

A Counterfactual Baseline for Assessing Future Environmental Impact: A Case Study of the Belt and Road Initiative

The impact of the Belt and Road Initiative (BRI) on the environment is an important but controversial topic. But assessing it faces a significant challenge for separating its policy impact from the overall effect of economic development that will also have environmental impacts. This paper attempts to provide an evolutionary and counterfactual baseline to evaluate the environmental impact of BRI, based on the distribution dynamics approach and the mobility probability plots (MPPs). Our estimation results suggest that while the majority of BRI economies will lower their emission levels compared with the world average, there are significant differences between BRI and non-BRI countrie’s emission patterns and dynamics. The majority of non-BRI economies will have lower emission levels than their BRI counterparts in the absence of BRI policy, indicating that the difference in future emissions between BRI and non-BRI countries should not be completely attributed to the environmental impact of BRI. Instead, BRI should take measures to prevent certain countries from moving upwards energy intensity paths through policy intervention, international cooperation, and an inclusive project assessment process.

Detecting conflicts of interest in credit rating changes: a distribution dynamics approach

In this study, we compare the adjustments of credit ratings by an investor-paid credit rating agency (CRA), represented by Egan-Jones Ratings Company, and an issuer-paid CRA, represented by Moody’s Investors Service, vis-à-vis conflict of interest and reputation. A novel distribution dynamics approach is employed to compute the probability distribution and, hence, the downgrade and upgrade probabilities of a credit rating assigned by these two CRAs of different compensation systems based on the dataset of 750 U.S. issuers between 2011 and 2018, that is, after the passage of the Dodd–Frank Act. It is found that investor-paid ratings are more likely to be downgraded than issuer-paid ratings only in the lower rating grades, which is consistent with the argument that investor-paid agencies have harsher attitudes toward potentially defaulting issuers to protect their reputation. We do not find evidence that issuer-paid CRAs provide overly favorable treatments to issuers with threshold ratings, implying that reputation concerns and the Dodd–Frank regulation mitigate the conflict of interests, while issuer-paid CRAs are more concerned about providing accurate ratings.

REGIONAL CONVERGENCE IN LARGE EMERGING ECONOMIES: A DISTRIBUTION DYNAMICS APPROACH

Rapid growth in large emerging economies has been spread unequally across their regions leading to growing income disparities. This paper examines the distribution of regional output per capita and the evolution of its shape in Brazil, China, India, and Russia from the mid-1990s to the mid-2010s. A comparative analysis of convergence is conducted using a nonparametric methodology. The results reveal different distribution dynamics across the four economies. Chinese regions with below-median output per capita have the highest probability of transitioning toward higher-income levels, while their Brazilian counterparts are trapped at the bottom of the distribution. Although India has the lowest and Russia one of the highest regional income inequalities, they display similar divergence patterns exemplified by high persistence at both ends of the distribution. Our findings indicate that government spending and the rule of law are the major driving forces behind regional convergence, except in Russia where they have the opposite effect. Innovation and property rights also promote convergence in China, but cause regional divergence in India.