The Unassuming Economist

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.”

From a paper by Julien Pascal:

“This paper reviews the literature examining the consequences of heterogeneity in macroeconomic modeling, especially within the context of monetary and fiscal policy transmission. This review reveals that heterogeneity can significantly alter the transmission mechanisms of monetary policy in macroeconomic models and suggests possible advantages from collaboration between fiscal and monetary policies. The paper also provides a critical evaluation of various analytical (limited-heterogeneity, history truncation, no-trade equilibrium) and numerical methods (forecasting rules, linearization in state-space or sequence-space, global methods) to solve macroeconomic models with heterogeneity, underscoring how these methods relate to each other, while emphasizing the need for a careful methodological choice based on specific circumstances.”

From a paper by Renáta Pitoňáková, Rudolf Kucharčík, and Ladislav Kabát:

“The accession to the European Union, several external shocks, and the questionable state interventions in the country’s business environment significantly impacted economic development of Slovakia. These phenomena were reflected in both the economic and social situation, namely the level of Gross domestic product (GDP) and rate of unemployment. The goal of our paper is to analyze the possible asymmetries in the unemployment-output relationship according to the Okun’s law. We used quarterly data to apply static and dynamic models in their symmetric and asymmetric forms (2009 Q1 – 2023 Q3). The results suggest that the labor market reacts more noticeably to GDP contraction than to GDP expansion. The outcomes are of interest to governing bodies managing labor market policy, primarily in the economic downturn, and for banks in controlling interest rates and inflation.”

From a paper by Kashif Nesar Rather and Mantu Kumar Mahalik:

“The attention surrounding the climate change has gained momentum over the last two decades, with significant stress on its consequential impact on gender inequality. Simultaneously, economies are caught in an environment of heightened uncertainty, potentially exerting influence on gender disparities. Within this framework, this study attempts to empirically investigate the implications of climate change and world uncertainty for gender inequality by using a balanced panel of 100 economies between 1995 and 2021. The novelty of this study lies in its adoption of Gender Inequality Index, a comprehensive measure quantifying gender disparity using three dimensions including reproductive health, economic empowerment, and labour market. Moreover, this study has adopted two different measures: the total ecological footprint to measure environmental pressures and ND-GAIN’s Vulnerability index to capture the climate change vulnerability, thereby ensuring comprehensive proxies for climate change dynamics. The estimated models also control for the effects of globalisation, economic growth, and education expenditure. The panel cointegration tests establish a significant long-run relationship between the variables of the study. Furthermore, the long-run results of PMG-ARDL estimation technique indicate that both climate change and world uncertainty contribute to increasing the gender disparities. Additionally, the results reveal that globalisation, economic growth, and education expenditure play crucial roles in diminishing gender disparities. The reliability of these findings is further confirmed by the PCSEs and DKSE estimation techniques. Moreover, the baseline findings obtained using total ecological footprint as a measure of climate change are consistent when climate change is proxied by Vulnerability Index. Potential policy suggestions for mitigating the detrimental gender ramifications stemming from climate change and rising world uncertainties are also discussed.”