The Unassuming Economist

From a paper by Jelena Momčilović and Mirjana Miletić:

“In this paper we showed how labour market factors are included in the macroeconomic model which the National Bank of Serbia uses for the medium-term inflation projection, thus enabling an insight into labour market trends, as well as an analysis of the link with other macroeconomic indicators, notably their effect on inflation. The estimates obtained by applying the Kalman filter indicate that NAIRU is still below the unemployment rate, suggesting a positive unemployment gap and showing that the labour market in Serbia is not exerting any major pressures on inflation. The paper also presents the results of testing the relevance of the hysteresis effect in the unemployment rate for Serbia. The hysteresis effect was confirmed by applying the unit root test and estimating the statistical significance of the stochastic trend in the NAIRU series.”

From a paper by François de Soyres, Simon Fuchs, Illenin O. Kondo, and Helene Maghin:

“We show how local worker flow adjustment margins yield a theory-consistent sufficient statistic
approximating the welfare effects of local shocks. Furthermore, we isolate a city’s insurance value
as this approximation’s second-order term. Leveraging rich labor flows data across occupations,
industries, and cities in France, we estimate spatial and non-spatial flows responses to local labor
demand shocks. Less economically diverse French cities experience deeper contractions in gross
outflows following negative shocks. In contrast, more economic concentration begets a modestly
larger increase in gross worker flows following positive shocks. Altogether, we uncover a sizable
welfare insurance gains from local economic diversity.”

From a new paper by Nicholas Apergis and Hany Fahmy:

“This paper explores the link between geopolitical risks and energy prices crash risk. Studying energy price crashes is important given the sharp fall in oil prices in 2008 and 2014. The analysis focuses on three energy markets: natural gas, oil, and coal, while it employs two measures: the negative coefficient of skewness and the down-to-up volatility, to construct proxies for crash risks. The period of examination is January 2000 to December 2023, whereas that for coal is January 2010 to December 2023. The study employs a modified version of the smooth transition autoregressive model. The results show that, within the modelling framework, coal and oil crash risks are driven by the cyclical behavior of geopolitical acts, whereas natural gas crash risks by geopolitical threats. Causality tests confirm the prediction that geopolitical tensions cause crash risks in energy markets. The results also confirm that the “Economic Activity Channel” is only valid for energy markets driven by geopolitical threats. Energy market regulators should be concerned about crash risks, given that the energy supply shows cyclical boom and bust cycles in prices and production. Crash risks could also potentially cause a fall in investments required to enhance energy efficiency.”

From a new paper by John Asker, Allan Collard-Wexler, Charlotte De Canniere, Jan De Loecker and Christopher R. Knittel:

“Market power reduces equilibrium quantities and distorts production, typically causing welfare losses. However, as Buchanan (1969) noted, market power may mitigate overproduction from negative externalities. This paper examines this in the global oil market, where OPEC’s market power affects oil production and carbon intensity. We estimate that from 1970 to 2021, OPEC’s market power reduced emissions by over 67 GtCO2, equating to $4,073 billion in climate damages and 17.8% of the carbon budget needed for the 1.5◦ C Paris Agreement target. This environmental benefit outweighs the welfare loss from distorted production allocation.”

From a paper by Sara El Aboudi, Youssef Jouali, Mounir El Bakkouchi and Abdellah Echaoui:

“In this study, we analyze the cross-impact of inflation, exchange rates and economic growth on income inequality in Morocco between 2000 and 2022, based on the GINI index as a measure of inequality. Its main objective is to understand how these macroeconomic variables influence income disparities. Our methodology is based on a VAR model to capture dynamic interactions between variables. To validate the robustness of the model, Granger causality tests and specification tests, including tests of homoscedasticity and autocorrelation of residuals, were used. The result is that inflation has a significant positive impact on income inequality, and exchange rate fluctuations directly influence inequality. Furthermore, economic growth helps to reduce inequality, although this effect depends on the distribution of the benefits of this growth. This study contributes to the existing literature by providing empirical evidence of the importance of macroeconomic stability and educational and fiscal policies in reducing income inequality.”