Codes

  • R code for implementing the methods in Sieve Estimation of Option-Implied State Price Density, Journal of Econometrics (Annals Issue: PI Day), 224 (2021), 88-112. 

  • Matlab program for implementing the methods in Likelihood Ratio Based Tests for Markov Regime Switching (with Fan Zhuo), Review of Economic Studies 88 (2021), 937-968. Additionally, the Matlab code for replicating the results in this paper is available here.

  • R code for replicating the results in Uniform Inference on Quantile Effects under Sharp Regression Discontinuity Designs, (with Jungmo Yoon), Journal of Business and Economic Statistics (2019), 625-647.

  • Matlab code for replicating the results in A Composite Likelihood Framework for Analyzing Singular DSGE Models, Review of Economics and Statistics 100 (2018), 916-932.

  • Matlab code for replicating the results in Frequency Domain Analysis of Medium Scale DSGE Models with Application to Smets and Wouters (2007) (with Denis Tkachenko), Advances in Econometrics: DSGE Models in Macroeconomics – Estimation, Evaluation and New Developments, 2012. 

  • Matlab code: Identification and Frequency Domain Quasi-maximum Likelihood Estimation of Linearized Dynamic Stochastic General Equilibrium Models (with Denis Tkachenko, Quantitative Economics, 2012). This code replicates the findings reported in Section 3.2 of the paper. [Dynare implementation: see p.120 of the linked document.]

  • R code for implementing the test in A Test against Spurious Long Memory (Journal of Business and Economic Statistics, 2011). The package contains a main file, an optional pre-whitening procedure (whitten-aic), and a data set for illustration.

  • R code: Estimating Structural Changes in Regression Ruantiles. This code is a companion to the following two papers: Oka, Tatsushi and Qu, Zhongjun (2011): “Estimating Structural Changes in Regression Quantiles,” Journal of Econometrics, 162, 248-267 and Qu, Zhongjun, (2008): “Testing for structural change in regression quantiles,” Journal of Econometrics, 146, 170-184. It contains procedures that (1) test and determine the number of breaks, (2) estimate break dates and their confidence intervals, and (3) estimate the coefficients and their standard errors. It can also be used to replicate the findings in the 2011 paper mentioned above.

  • Matlab code: Estimating and Testing Structural Changes in Multivariate Regressions (with Pierre Perron, Econometrica, 2007). This version: January 2022.
    This code contains procedures to do the following for a multi-equations model, allowing multiple structural changes and arbitrary restrictions on the coefficients: 1) Estimate the model and construct confidence intervals for the estimates (break dates and coefficients); 2) Compute various tests for the presence of breaks; 3) Estimate and construct confidence intervals for the break dates of a two-equation locally ordered break model (and construct the tests for the presence of breaks). This is a direct Matlab translation of the Gauss code of Qu, Z. and P. Perron (2007, Econometrica). This Matlab version was developed by Dr. Davaajargal Luvsannyam at The Bank of Mongolia.

  • GAUSS code: Estimating Restricted Structural Change Models (with Pierre Perron, Journal of Econometrics, 2006). This code contains procedures to do the following for a single equation model that allows multiple structural changes and arbitrary restrictions on the coefficients: 1) Estimate the model and construct confidence intervals for the estimates (break dates and coefficients); 2) Compute the sup-F test for breaks with restrictions; 3) Simulate the critical values of the restricted structural change sup-F test.

  • Gauss Code 1 and Gauss Code 2 for Searching for Cointegration in a Dynamic System (Econometrics Journal 2007). File 1: Procedures to implement the test statistics. File 2: Procedures to simulate additional critical values.