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Modeling and estimating persistent discrete data can be challenging. In this paper, we use an autoregressive panel probit model where the autocorrelation in the discrete variable is driven by the autocorrelation in the latent variable. In such a non-linear model, the autocorrelation in an unobserved variable results in an intractable likelihood containing high-dimensional integrals.

We examine the ability of the simple linear-quadratic model under rational expectations to explain dynamic behaviour of aggregate Canadian imports. In contrast to authors of previous studies who examine dynamic behaviour using the LQ model, we estimate the structural parameters using the Euler equation in a limited information framework that does not require an explicit solution for the model's control variables in terms of the exogenous forcing variables.

This paper derives analytical gradients for a broad class of regime-switching models with Markovian state-transition probabilities. Such models are usually estimated by maximum likelihood methods, which require the derivatives of the likelihood function with respect to the parameter vector. These gradients are usually calculated by means of numerical techniques. The paper shows that analytical gradients […]

This paper proposes a novel asymptotic least-squares estimator of multi-country Gaussian dynamic term structure models that is easy to compute and asymptotically efficient, even when the number of countries is relatively large—a situation in which other recently proposed approaches lose their tractability.

Over the past 15 years, long-term interest rates have declined to levels not seen since the 1970s. This paper explores possible shifts in global savings and investment that have led to this fall in the world real interest rate.

Model risk is a constant danger for financial economists using interest-rate forecasts for the purposes of monetary policy analysis, portfolio allocations, or risk-management decisions. Use of multiple models does not necessarily solve the problem as it greatly increases the work required and still leaves the question "which model forecast should one use?"

We construct a dataset on Federal Reserve and Bank of Canada non-rate announcement events to provide novel insights into how foreign and domestic monetary policy communications affect the financial markets of open economies. We find that Fed non-rate communications have a stronger impact on long-term interest rates and stock futures, while Bank of Canada communications are relatively more important for short-term interest rates and the exchange rate.

We revisit an old question: how do financial constraints affect the transmission of monetary policy to the real economy? To answer this question, we propose a simple empirical strategy that combines firm-level employment and balance sheet data, identified monetary policy shocks and survey data on financing activities.

Do bond risk premiums influence the effects of debt maturity operations? Using a model with realistic bond risk premiums, we show that maturity operations have sizable effects on expected inflation and output when the central bank passively responds to inflation and the fiscal authority weakly responds to the debt level.

We introduce behavioral learning equilibria (BLE) into DSGE models with boundedly rational agents using simple but optimal first order autoregressive forecasting rules. The Smets-Wouters DSGE model with BLE is estimated and fits well with inflation survey expectations. As a policy application, we show that learning requires a lower degree of interest rate smoothing.