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We conduct surveys to study how consumer spending responds to higher inflation expectations. Most respondents spend the same, sticking to fixed budget plans or not considering inflation for spending decisions. About 20% decrease spending because they feel poorer and cut spending to invest in inflation-proof assets. Very few increase spending.

Since the global financial crisis, advanced-economy wage growth has been generally low relative to past recoveries, especially after accounting for the evolution of labour market conditions over this period. This paper investigates a variety of potential explanations for this weakness, drawing on findings from the literature as well as analysis of recent labour market data in advanced economies.

This paper theoretically and empirically examines the price impacts of liquidations in DeFi and how different liquidation mechanisms affect the price impacts.

We present two models for long-term inflation expectations and inflation risk premiums for Canada.

This paper proposes a method for estimating the joint distribution of two or more variables when only their marginal distributions and the distribution of their aggregates are observed. Nonparametric identification is achieved by modelling dependence using a latent common-factor structure.

This paper predicts phases of the financial cycle by using a continuous financial stress measure in a Markov switching framework. The debt service ratio and property market variables signal a transition to a high financial stress regime, while economic sentiment indicators provide signals for a transition to a tranquil state.

It is widely understood that the real price of globally traded commodities is determined by the forces of demand and supply. One of the main determinants of the real price of commodities is shifts in the demand for commodities associated with unexpected fluctuations in global real economic activity.

This article examines what market conditions lead to extreme losses in global financial systems. Using a reverse stress testing approach, it introduces two measures of systemic risk by starting from the tail losses and working backward to identify the events most closely associated with them.

How much capital do banks need as a buffer to absorb severe shocks? By using historical stock market data, market-based stress tests help estimate the magnitude of capital buffers necessary to absorb severe but plausible shocks.

Statistical inference--both estimation and testing--for stochastic volatility (SV) models is known to be challenging and computationally demanding. We propose simple and efficient estimators for SV models with conditionally heavy-tailed error distributions, particularly the Student’s t and Generalized Exponential Distributions (GED). The estimators rely on a small set of moment conditions derived from ARMA-type representations of SV models, with an option to apply “winsorization” to improve stability and finite-sample performance. Except for the degrees of-freedom parameter, closed-form expressions are available for all other parameters, extending Ahsan and Dufour (2019, 2021), thus eliminating the need for numerical optimization or initial values. We derive the estimators’ asymptotic distribution and show that, due to their analytical tractability, they support reliable, and even exact, simulation-based inference via Monte Carlo or bootstrap methods. We assess their performance through extensive simulations and demonstrate their practical relevance in financial return data, which strongly reject the normality assumption in favor of heavy-tailed models.