The Unassuming Economist

From a paper by João Tovar Jalles, Carola Pessino, and Ana Cristina Calderon:

“Widening income disparities, higher corruption, and increased informality in many emerging market and developing economies (EMDEs)—all with pressing and mounting fiscal problems—have rekindled interest in the empirical analysis of the key factors determining the occurrence of fiscal consolidations. Using discrete choice models, this paper examines the drivers of fiscal consolidation episodes in a sample of 148 EMDEs between 1980 and 2019, with a focus on Latin American and Caribbean countries. Inequality does not seem to drive consolidations—which are more likely during good economic times—while more informality increases the probability of their occurrence and corruption decreases it. In turn, when examining the drivers of successful consolidations, larger income inequality acts as a boost, while informality is a hinderance. In fact, while the size of the public investment multiplier in Latin America and the Caribbean is larger than in other regions, when informality is high, the multiplier effect is reduced to a much lower and insignificant magnitude. Results are robust to several sensitivity and robustness tests.”

From a paper by Olufemi G. Onatunji:

“The growing imperative to attain equitable income distribution has compelled international organizations and the academic community to make a collaborative commitment towards alleviating the escalating income inequality experienced worldwide. While there has been a notable development of interest among scholars regarding the nexus between fiscal policy and income inequality, the empirical scrutiny on the contributing role of fiscal policy and institutional quality remains scant in the literature. The present study complements the existing literature by investigating the tripartite nexus between fiscal policy, institutional quality, and income inequality in SSA, which has received no empirical attention in the literature. This study utilizes an advanced econometric technique, the cross-sectional autoregressive distributed lag (CS-ARDL) approach, which addresses cross-sectional dependency and heterogeneity issues for the panel dataset during 1990–2015. The empirical results demonstrate that economic growth, population growth, and government tax exacerbate income inequality, whereas education, government expenditure, and institutional quality metrics mitigate income inequality in SSA countries in the short and long run. The findings also indicate that the performance of institutional quality settings in SSA is significant for fostering efficient fiscal policy, thus improving equitable income distribution. These findings offer substantial, valuable insights and policy implications for policymakers in SSA, which may inform the design and formulation of sustainable development strategies to achieve equitable income distribution.”

From a paper by Cong Minh Huynh, and Khanh Nam Pham:

“In a comprehensive study across 32 Asian countries and territories spanning 2002–2018, we unveil the surprising impact of uncertainty on income inequality. Contrary to conventional expectations, our analysis reveals a fascinating trend: heightened uncertainty appears to wield a dual impact on income distribution. While it diminishes the income shares of both the richest and the poorest segments of society, the reduction is far more pronounced among the wealthiest quintile. Surprisingly, this outcome leads to a lessening of income inequality. The results are robust with fixed effects, feasible generalized least squares, and especially panel vector autoregression (PVAR) to tackle endogeneity concerns. The findings imply that in a more stable environment, the rich enjoy a higher growth of income than the poor, while in higher uncertainty, the income of the rich drops more dramatically than that of the poor. Thus, policymakers should take this into consideration for appropriately making income redistribution policies during normal and crisis periods, especially considering the varying impact of uncertainty on different segments of society.”

From a new paper by Efrem Castelnuovo, Kerem Tuzcuoglu, and Luis Uzeda:

“We propose a new empirical framework to estimate sectoral uncertainty from data-rich environments. We jointly decompose the conditional variance of economic time series into a common, a sector-specific, and an idiosyncratic component. By specifying a hierarchical-factor structure to stochastic volatility modeling, our framework combines both dimension reduction and flexibility. To estimate the model, we develop an efficient Markov Chain Monte Carlo algorithm based on precision sampling techniques. We apply our framework to a large dataset of disaggregated industrial production series for the U.S. economy. Our findings suggest that: (i) uncertainty is heterogeneous at a sectoral level; and (ii) durable goods uncertainty may drive some business cycle effects typically attributed to aggregate uncertainty.”

From a paper by Borivoje D. Krušković:

“This paper analyzes the unanalized topic in macroeconomic (monetary) politics, which is the emergence of the currency crisis as a consequence of targeting inflation. Many central banks adopted inflation targeting under a pressure from the IMF. Sudden depreciation of exchange rate which results from a fall of foreign exchange reserves to a critically low level (below an optimal level) leads to currency crisis due speculative attack. The most widely used model in the decision of creating process of monetary policy in inflation targeting regime is the macroeconomic model of a small open economy from the group New Keynesian model.”