The Unassuming Economist

From a paper by Washingtone Onyango, Socrates Majune, and Patricia Naluwooza:

“This study analyzes the effect of China’s import dominance on Africa’s structural transformation, measured through the Shapley decomposition approach. A pooled mean group Autoregressive Distributed Lag (PMG-ARDL) model is analyzed using panel data from 1995–2018 for 21 countries. We find that Chinese imports of goods and services, like those from the rest of the world, increase Africa’s structural transformation in the long-run. However, the magnitude of the coefficient for China is larger than that of the rest of the world for both goods and services (total). The Chinese impact on Africa’s structural transformation is mainly through capital goods and other commercial services (such as ICT, financial, and construction), whose coefficients are larger than those of the rest of the world. Imposing barriers on Chinese imports is not a viable option for African countries. Instead, they should pursue policies that enrich the manufacturing sector, including adopting an Africa-wide trade agreement.”

From a paper by Yongjian Lyu, Heling Yi, Mo Yang, Yihan Zou, Ding Li, Zhilong Qin:

“Financial uncertainty shocks are emerging as potential drivers for the spillovers of risk originating from the oil market into the stock market, with the increasing financialization of the oil market. This paper explores this phenomenon and provides compelling findings. First, the oil market generates substantial risk spillovers to the stock market, reaching a peak amid the COVID-19 crisis. Second, according to the backtesting results, the ΔCoVaR values derived from the Student-t Copula model reflect the true level of such risk spillovers. Third, shocks to financial uncertainty increase systemic risk by causing risk to spill over from the oil to the stock market, with larger spillovers occurring during periods of increased economic vulnerability. Finally, financial uncertainty shocks are the fundamental drivers of variance changes in risk spillovers, making a greater contribution than macroeconomic uncertainty shocks, according to the time-varying forecast error variance decomposition.”

From Brookings:

“2025 will be a critical juncture for Africa’s trajectory. New political leadership in both the African Union and the United States coincides with the urgent need to meet the looming 2030 deadline for the Sustainable Development Goals, to accelerate implementation of the African Continental Free Trade Area, and to modernize and renew the African Growth and Opportunity Act—a cornerstone of the U.S. Africa trade relationship—currently set to expire in September 2025. Paired with an escalating climate crisis and the reverberations of conflict and global economic instability, these dynamics will require bold and coordinated policy action to address Africa’s unique challenges while leveraging its vast potential.

This special edition of Foresight Africa—the flagship annual report of the Africa Growth Initiative at Brookings—extends its focus from one year to five and offers cutting-edge insights and actionable strategies from heads of government, global institutions, continental and multilateral institutions, as well as leading Brookings scholars and other high-profile policymakers, business figures, and civil society leaders.

Together, the report’s six chapters offer a comprehensive vision for Africa’s next chapter—a future driven by African leadership, bold innovation, and inclusive growth.”

Continue reading here.

From The Indian Express:

“While there is little room for complacency, Indian growth is inclusive on most counts

Inclusive growth is critical for us to become a developed nation by 2047. A leading indicator is improvements in the living standards of those at the bottom of the economic pyramid. Another is the direction of changes in income inequality. Apart from being a moral issue, distribution of national income determines the composition of aggregate demand and hence, the allocation of resources to different production processes, which, in turn, will affect the pace towards Viksit Bharat.”

Continue reading here.

From a paper by Emmanouil Sofianos, Christos Alexakis, Periklis Gogas, and Theophilos Papadimitriou:

“This paper aims to forecast deviations of the US output measured by the industrial production index (IPI), from its long-run potential output, known as output gaps. These gaps are important for policymakers when designing relevant economic policies, especially when a negative output gap may show economic slack or underperformance, often associated with higher unemployment and low inflation. We use a dataset that includes 32 explanatory economic and financial variables and 18 lags of the IPI, spanning the period from 2000:1 to 2022:12, resulting in 50 variables and 276 monthly observations. The dataset is fed to five well-established machine learning (ML) methods, namely decision trees, random forests, XGBoost, long short-term memory (LSTM) and support vector machines (SVMs), coupled with the linear, the RBF and the polynomial kernel. Moreover, we use the standard elastic net logit method from the area of econometrics as a benchmark. Our results indicate that the tree-based ML techniques perform better in-sample, and the best overall forecasting model is the XGBoost achieving an out-of-sample accuracy of 91.67%.”