Robust Inference Via Heteroskedasticity in Linear Models

Omer Faruk Akbal and Max-Sebastian Dovi

No 2026/100, IMF Working Papers from International Monetary Fund

Abstract: We study inference via heteroskedasticity in linear models commonly used for macroeconomic policy analysis, where covariate endogeneity must often be addressed with limited time and data. Our framework nests standard heteroskedasticity-based approaches, allows for new non-nested restrictions, and does not require ex-ante regime labelling. We propose an easily implementable weak-identification-robust test and derive sufficient conditions for its validity. Simulation results show good size and power properties in a wide range of settings. Empirical applications to the fuel-price passthrough in Sierra Leone, the effect of remittances on consumption in the Philippines, and exchange-rate passthroughs in many countries illustrate the versatility and scalability of our approach.

Keywords: Heteroskedasticity; weak identification; Anderson-Rubin; two-step inference; IMF working papers; regime labelling; simulation result; views of the IMF; Inflation; Fuel prices; Remittances; Exchange rates; Consumption; Global (search for similar items in EconPapers)
Pages: 38
Date: 2026-05-22
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