The Unassuming Economist

From a paper by Antoine Gaudin, Brendan Harnoys-Vannier, and Martin Kessler:

“In the context of the ongoing review of the Debt Sustainability Analysis (DSA) for Low-Income
Countries (LICs), this paper seeks to help shed light on IMF and World Bank macroeconomic
projections. DSAs are central to the financial architecture of developing countries. Yet, the ways the
projections are performed are rarely accessible to outside researchers.

The first contribution of this paper is to provide a newly constructed database of 605 DSAs
conducted from 2013 to 2024. It contains all the information of all published DSAs for LICs in Tables 1
(macro-economic and fiscal) and 2 (external debt dynamics), as well as the shock scenarios. It will be
updated regularly.

The second contribution of the paper is to analyze forecast errors concerning public and external
debt, as well as the main macroeconomic components. It highlights results on large optimistic biases,
with a 10 percentage point underestimation of the trajectory of the debt-to-GDP ratio on average after
5 years. Decomposing this result, it finds that:

1. Larger countries tend to be more affected by significant positive biases. Small Island
   Developing States (SIDS) and vulnerable countries tend to be more accurately forecasted. We
   interpret this finding as showing the integration of past shocks in the baseline.
   
2. It’s mostly fiscal: The main driver of forecast errors is the underestimation of primary deficits, followed by overestimated GDP growth. In particular, forecasting errors on primary deficits stem from overestimated fiscal revenues.
   
3. Mixed results post-2017 reform: While the 2017 reform introduced tools aimed at enhancing forecast realism, biases have persisted. This is evidence of some limited (non-statistically significant) improvements by reducing the optimism bias. This pleads for further disclosure of assumptions. However, given that they were rolled out in 2018, and that COVID-19 made projections difficult, we also caution against too broad interpretation of those results.
   
4. DSAs designed in the context of programs perform better on public debt, but worse on deficits: This tends to show that the IMF tends to overestimate the political feasibility of a program. We find some support for the idea that in LICs, the multipliers are still underestimated.
   
5. Influence of country-specific factors: The study identifies institutional, structural, and cyclical factors influencing these biases, including governance quality, economic diversification, and global economic conditions. Countries reliant on commodity exports tend to have significant forecast biases, particularly optimistic projections for both public and external debt ratios. Countries with fragile governance or in conflict display more pessimistic forecasts for primary deficits and external debt, but overly optimistic growth projections. Countries that have had market access and have build-up debt stocks toward defending market access.
   
6. Recession conditions: DSAs conducted during recessions are associated with strong optimism in public and external debt ratios as well as real GDP growth. This suggests both a tendency to overplay rebound effects and a misconception of the way macroeconomic effects transmit over various phases of the business cycle.
   
   
   Optimism bias is very hard to control, but it can have large policy consequences on the IMF and its members. By publishing more information on its DSAs, the IMF and the World Bank have allowed outside scrutiny. The database we are publishing hopefully provides the tools to outside researchers to help this scrutiny, and we hope that this paper is a first example of such exploration.

From a paper by Óscar Peláez-Herreros:

“We develop the first disaggregation of Okun’s law that quantifies all of the information that is subsumed within its coefficients. The proposed method decomposes the coefficients into the sum of the direct effect of the change in output upon the unemployment rate, plus the indirect effects of the variations in the output per hour worked, the hours worked per employed person, the participation rate, and the size of the working-age population. With quarterly data for the United States from 1948 to 2024, we found that the value of the intercept in Okun’s relation is determined by the increases in working-age population and output per hour of work, along with the decrease in the number of hours worked per employed person, plus the growth of the participation rate until the 1990s and its subsequent decline. For its part, the slope, that is, the value of Okun’s coefficient, depends mainly upon the variations in output per hour of work and the hours per employed person. The other factors were scarcely relevant. Changes in these components caused the Okun’s relation to vary over time, showing a greater sensitivity of the unemployment rate to variations in production since the 2008 crisis.”

From a paper by Neeraj Nautiyal, Mobeen Ur Rehman, Rami Zeitun, and Xuan Vinh Vo:

“We investigate how socially responsible investment (SRI) funds respond to different oil-induced price shocks, using Ready’s (2018) approach. Using daily data for six SRI indices from March 8, 2016, to November 29, 2024, we apply wavelet coherence and nonlinear causality methods to analyze the time-frequency relationship between oil shocks and SRI fund performance across different market states. Our findings reveal that supply and risk shocks play a significant role in driving the co-movement between oil price dynamics and SRI funds’ behavior returns, particularly at medium and lower frequencies, respectively. Risk shocks exhibit a systemic influence, consistently dominating supply and demand shocks, especially in the pre-2021 period and during the COVID-19 pandemic, though their effects fizzle out in stable market conditions. Quantile causality estimates confirm the strong predictive power of risk shocks, particularly at lower quantiles. Our work presents practical implications for ethical investors, dealing with oil-related market risks.”

From a paper by Cars Hommes, and Sebastian Poledna:

“This study investigates the potential of agent-based modelling to forecast economic crises, addressing the failure of standard macroeconomic models to predict the 2008 financial crisis and capture crisis dynamics. While dynamic stochastic general equilibrium models have incorporated financial frictions, solving them typically requires linearisation around steady states, which suppresses the non-linear feedback loops through which crises emerge. Agent-based models avoid this limitation by numerically simulating heterogeneous agents, preserving non-linear dynamics without approximation. We develop such an agent-based model for the euro area and show that out-of-sample forecasts outperform benchmarks. We further demonstrate that the model can forecast economic crises without exogenous shocks and accurately reproduce crisis dynamics. The model endogenously predicts the onset of the Great Recession, explains the persistence of the sovereign debt crisis, and reproduces the sharp contraction and swift recovery of the COVID-19 recession. The findings suggest that preserving non-linear feedback loops is essential for crisis prediction.”

From a paper by Tayebeh Chaman, Ali Asghar Salem, Abbas Shakeri Hossein Abad, and Teymour Mohammadi:

“The inflation targeting regime, by emphasizing transparency, accountability, and anchoring inflation expectations, leads to improved inflation control, a reduction in economic instability, and the creation of a favorable environment for economic growth, productive investment, and lower income inequality. Therefore, the objective of the present study is to investigate the role of inflation targeting in income distribution across a sample of 39 countries, including 7 inflation-targeting and 32 non-inflation-targeting countries, using a difference-in-differences approach over the period 1995–2023. The findings indicate that the implementation of an inflation-targeting regime has a negative and statistically significant effect on the Gini coefficient, thereby reducing income inequality in the treatment-group countries relative to the control group. In addition, per capita GDP, the share of the agricultural sector in GDP, and foreign direct investment have negative and significant effects on income inequality, while the trade share of GDP has a positive and significant effect. Overall, the results suggest that adopting an inflation-targeting regime in countries experiencing high inflation and ineffective monetary policy frameworks can mitigate the adverse effects of inflation on income distribution. Thus, it is recommended that central banks in such countries implement an inflation-targeting framework to enhance macroeconomic stability, promote investment, and reduce income inequality.”