In this paper, I develop a population-based Markov chain Monte Carlo (MCMC) algorithm known as parallel tempering to estimate dynamic stochastic general equilibrium (DSGE) models. Parallel tempering approximates the posterior distribution of interest using a family of Markov chains with tempered...

We study the falsifiability and identification of Quantal Response Equilibrium (QRE) when each player's utility and error distribution are relaxed to be unknown non-parametric functions. Using variations of players' choices across a series of games, we first show that both the utility function...

The naive Bayes approach is one of the most popular methods used for classification. Nevertheless, how to test its statistical significance under an ultra-high-dimensional (UHD) setup is not well understood. To fill this important theoretical gap, we propose a novel testing statistic with a...

In this paper, we consider the visualization and statistical modeling of financial data (e.g., sales, assets) for many global firms which are listed and delisted. This study presents an exploratory data analysis carried out in the R programming language. The results show that a log-linear model...

We present a novel database of real-time data and forecasts from the Bank of Canada's staff economic projections. We then provide a forecast evaluation for GDP growth and CPI inflation since 1982: we compare the staff forecasts with those from commonly used time-series models estimated with...

This paper develops and estimates a model of firm-level fixed capital investment when firms face borrowing constraints. Dynamically optimal investment functions are derived for the firms with and without financial constraints. These policy functions are then used to construct the likelihood of...

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...

How wrong could policymakers be when using linearized solutions to their macroeconomic models instead of nonlinear global solutions? This question became of much practical interest during the Great Recession and the recent zero lower bound crisis. We assess the importance of nonlinearities in a...