The Unassuming Economist

From a paper by Surjit S. Bhalla, Karan Bhasin, and Prakash Loungani:

“There seems to be a consensus that the inflation targeting framework adopted in India in 2016 has been successful in taming inflation. A comprehensive analysis of inflation targeting should be based on the impact on inflation dynamics, expectations and implications for growth. We illustrate the strong downward time-trend in India’s inflation dynamics coinciding with the inflation targeting regime. Trend inflation levels in India and other emerging market economies also suggest a downward trajectory regardless of the adoption of inflation targeting. Thefore, it is difficult to conclusively establish that adoption of inflation targeting in India led to a moderation in inflation or anchoring of inflation expectations. On expectations, there is some evidence of anchored household expectations, however, this anchoring predates the formal adoption of inflation targeting. Long-term expectations in India have remained firmly anchored since early 2000s. In terms of growth, the high real interest rates policy followed during the initial years of inflation targeting to establish credibility of IT regime adversely affected India’s growth dynamics.”

From a paper by Panagiotis Delis, and Georgios Kontogeorgos:

“Evaluating macroeconomic forecasts for their unbiasedness and efficiency is essential for policymakers, economists, and investors. The degree to which these stakeholders incorporate expectations into their decision-making processes depends heavily on how these forecasts have been formed. Existing methodologies do not explicitly address critical dimensions, such as the variability of bias across target events and forecast horizons, the forecast errors’ heteroscedasticity, and the potential state-dependence in bias. More importantly, they encounter difficulties during high-uncertainty periods, which can lead to inaccurate inference due to the presence of outliers. Apart from generalising the unbiasedness tests, this study contributes to the literature on both strong and weak efficiency by incorporating these aspects. Finally, the proposed methods are applied to the expectations of a crucial survey of the US economy, namely, the Survey of Primary Dealers (SPD). The findings from this application indicated that interested parties should investigate unbiasedness and efficiency in an outlier-robust way, while also allowing for greater flexibility in the methods regarding the variables and periods examined.”

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 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 Harold Glenn A. Valera, Cymon Kayle Lubangco, and Mark J. Holmes:

“We propose a new measure of revisions to consumer inflation expectations using repeated cross-sections rather than requiring panel data. We calculate the value of group average expectations in a prior period as a proxy for what an individual’s expectations might have been using micro data in the Philippines for Q1 2010 to Q2 2024. In contrast to existing mixed evidence, the resulting revisions show sensitivity to price changes in 14 food and energy goods. The equivalence testing finds that the group-based coefficients are valid, as they are: (a) different from an overall sample average-based revision results with Philippine data and (b) similar to rotating panel-based revision results using data from the Michigan Survey of US households. Using Philippine data, we also provide new evidence of significant effects of a firm’s frequency of price changes on expectation revisions.”