Parameter Estimation and Inference in a Cointegrating Regression
Overview
Cointegration methods are widely used in empirical macroeconomics and empirical finance. It is well known that in a cointegrating regression the ordinary least squares (OLS) estimator of the parameters is super-consistent, i.e. converges at rate equal to the sample size T. When the regressors are endogenous, the limiting distribution of the OLS estimator is contaminated by so-called second order bias terms, see e.g. Phillips and Hansen (1990) DOI:10.2307/2297545. The presence of these bias terms renders inference difficult. Consequently, several modifications to OLS that lead to zero mean Gaussian mixture limiting distributions have been proposed, which in turn make standard asymptotic inference feasible. These methods include the fully modified OLS (FM-OLS) approach of Phillips and Hansen (1990) DOI:10.2307/2297545, the dynamic OLS (D-OLS) approach of Phillips and Loretan (1991) DOI:10.2307/2298004, Saikkonen (1991) DOI:10.1017/S0266466600004217 and Stock and Watson (1993) DOI:10.2307/2951763 and the new estimation approach called integrated modified OLS (IM-OLS) of Vogelsang and Wagner (2014) DOI:10.1016/j.jeconom.2013.10.015. The latter is based on an augmented partial sum (integration) transformation of the regression model. IM-OLS is similar in spirit to the FM- and D-OLS approaches, with the key difference that it does not require estimation of long run variance matrices and avoids the need to choose tuning parameters (kernels, bandwidths, lags). However, inference does require that a long run variance be scaled out. This package provides functions for the parameter estimation and inference with all three modified OLS approaches. That includes the automatic bandwidth selection approaches of Andrews (1991) DOI:10.2307/2938229 and of Newey and West (1994) DOI:10.2307/2297912 as well as the calculation of the long run variance.
Install
Health
NOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Maintainer: ‘Philipp Aschersleben <aschersleben@statistik.tu-dortmund.de>’
Found the following URLs which should use \doi (with the DOI name only):
File ‘cointReg.Rd’:
http://dx.doi.org/10.2307/2297545
http://dx.doi.org/10.2307/2298004
http://dx.doi.org/10.1017/S0266466600004217
http://dx.doi.org/10.2307/2951763
http://dx.doi.org/10.1016/j.jeconom.2013.10.015
File ‘cointRegD.Rd’:
http://dx.doi.org/10.2307/2298004
http://dx.doi.org/10.1017/S0266466600004217
http://dx.doi.org/10.2307/2951763
File ‘cointRegFM.Rd’:
http://dx.doi.org/10.2307/2297545
File ‘cointRegIM.Rd’:
http://dx.doi.org/10.1016/j.jeconom.2013.10.015
File ‘getBandwidth.Rd’:
http://dx.doi.org/10.2307/2938229
http://dx.doi.org/10.2307/2297912- NOTE11 OK, 2 NOTENow
- NOTE12 OK, 2 NOTE2026-03-10
Documentation
- Help pages
- 16includes a package overview page
- Examples that run
- 100%15 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 89%
- Return-value docs
- 100%
- Help pages citing references
- 31%
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Dependencies
Installing cointReg adds 3 packages (3 with compiled code, 483 KB of source tarballs). Heaviest: checkmate 247 KB, matrixStats 207 KB, backports 29 KB.
Code & Tests
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- RR 4.6.0 released · 2026-04-24
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- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- RR 3.5.0 released · 2018-04-23
- RR 3.4.0 released · 2017-04-21
- 0.2.0Latest
- 0.1.02016-06-06
- RR 3.3.0 released · 2016-05-03
Package metadata
- First published
- 2016-06-06
- Total releases
- 2 / 10 yrs
- License
- GPL-3 OSI
- Download size
- 73 KB
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