The Unassuming Economist

From a paper by Nicolas Chatelais, Arthur Stalla-Bourdillon, and Menzie D. Chinn:

“After the Covid-shock in March 2020, stock prices declined abruptly, reflecting both the
deterioration of investors’ expectations of economic activity as well as the surge in aggregate risk
aversion. In the following months however, whereas economic activity remained sluggish, equity
markets sharply bounced back. This disconnect between equity values and macro-variables can
be partially explained by other factors, namely the decline in risk-free interest rates, and, for the
US, the strong profitability of the IT sector. As a result, an econometrician trying to forecast
economic activity with aggregate stock market variables during the Covid-crisis is likely to get
poor results. The main idea of the paper is thus to rely on sectorally disaggregated equity
variables within a factor model to predict future US economic activity. We find, first, that the
factor model better predicts future economic activity compared to aggregate equity variables or to
usual benchmarks used in macroeconomic forecasting (both in-sample and out-of-sample).
Second, we show that the strong performance of the factor model comes from the fact that the
model filters out the “expected returns” component of the sectoral equity variables as well as the
foreign component of aggregate future cash flows, and that it also over-weights upstream and
“value” sectors that are found to be closely linked to the future state of the US business cycle.”

From a paper by William Ginna:

“This paper presents a non-linear extension of the Phillips Curve by estimating a Local Projections (LP) panel model using data from 14 countries between January 1999 and December 2023. The non-linearity arises from the asymmetric effects of the El Niño–Southern Oscillation (ENSO), which alternates between El Niño and La Niña phases. The findings highlight two key dimensions of this asymmetry: slope and curvature. In terms of slope, the Phillips Curve is significantly steeper during La Niña episodes, with inflation responding more strongly and persistently to unemployment gaps. In terms of curvature, the inflation response under La Niña builds over time, reflecting non-linear propagation dynamics. In contrast, the Phillips Curve is flatter and responses are weaker and less persistent during El Niño phases. These findings underscore the importance of incorporating ENSO variability into macroeconomic models.”

From a paper by Cameron Haas, Mateo Hoyos, Emiliano Libman, Guilherme K. Martins, and Arslan Razmi:

“After decades of low and stable inflation, recent global events —such as the COVID-19 pandemic and the Russian invasion of Ukraine —triggered a resurgence in inflationary pressures, prompting central banks worldwide to tighten monetary policy. This paper examines whether monetary policy effectively curbs inflation by employing a trilemma-based identification strategy on a panel dataset of 36 developing and 8 developed economies from 1990 to 2017. Using higher-frequency monthly data, we improve on traditional quarterly or annual approaches by more precisely capturing central bank responses. By applying our theory-driven, trilemma-based identification strategy to a sample of developing countries, we bring novel insights to existing literature. Our findings indicate that monetary policy shocks have significant but impermanent effects on inflation. A 100 basis point interest rate hike lowers the price level by 3.7% at its peak after six months, with effects fading within 18 months. Crucially, our results do not exhibit the “price puzzle,” reinforcing the credibility of our identification strategy. Additionally, we find that monetary policy effects are state-dependent, with stronger disinflationary impacts during high-inflation periods and in economies with lower GDP per capita or higher commodity export dependence. These findings highlight the heterogeneity in monetary policy transmission, underscoring the need for tailored policy responses across different economic contexts.”

From a paper by Andrew Filardo, Mr. R. G Gelos, and Thomas McGregor:

“This paper develops a new approach for exploring the effectiveness of foreign currency intervention, focusing on real exchange cycles. Using band spectrum regression methods, it examines the role of macroeconomic fundamentals in determining the equilibrium real exchange rate at short-, medium-, and low frequencies. Next, it assesses the effectiveness of FX intervention depending on the degree of cycle-specific misalignments for 26 advanced- and emerging market economies, covering the period 1990–2018, and using different techniques to mitigate endogeneity concerns. Evidence supports the hypothesis that central banks can lean effectively against short-run cyclical misalignments of the real exchange rate. The effects are present in quarterly data—i.e., at policy-relevant horizons. The effectiveness of intervention rises with the size of the misalignment, and with the duration of one-sided interventions. FX sales appear to be somewhat more effective than FX purchases, and intervention is less effective in more liquid FX markets.”

From a paper by Saban Nazlioglu, Sinem Pinar Gurel, Sevcan Gunes, Tugba Akin, Cagin Karul & Muhsin Kar:

“The growing empirical literature documents evidence on increasing global inflation co-movement across countries over time; however, little is known about the quantile co-movement structure of inflation. By introducing quantile factor model for a global sample of 151 countries from 1970 to 2023, this study provides new insights with respect to inflation co-movement. The quantile factor analysis sheds light on that (i) global inflation has a quantile-dependent factor structure, with different behavior in low, mild/stable, and high inflation periods; (ii) inflation shows an asymmetric co-movement pattern, with a decreasing degree in low and high inflation periods in comparison with stable inflation period; (iii) while interest rate and economic activity are the underlying observables for the latent quantile factors in low and stable inflation periods, commodity prices also become an underlying observable in high inflation period; and finally (iv) using quantile factors is nontrivial in improving density forecast of inflation in both developed and emerging markets.”