This is where you can find code and/or data sets that I’ve built for past research projects. This material is copyrighted; please feel free to use it for your non-profit research. Acknowledgements and citations to this work are warmly appreciated. This material is unsupported. Looking for something that you can’t find? Just e-mail me….I’ve probably overlooked it.
Reconciling GDE and GDI
This is the replication file for Jacobs, Sarferez, Sturm and van Norden (forthcoming) Journal of Business and Economic Statistics. The code was written by Samad Sarferez and should also be available via the journal page.
Greenbook Fiscal Forecasts and Data
This is the replication file for Croushore and van Norden (2018) Review of Economics and Statistics. It includes the source data collected from Federal Reserve Board Staff Greenbooks. Programs run under a combination of GAUSS and WinRATS, and a variety of different data tables are created.
This collection allows you to reproduce many of the additional results in Croushore and van Norden (forthcoming) International Journal of Forecasting .
More recently, the Federal Reserve Board has started publishing “accessible” versions of the Greenbooks, Bluebooks and Tealbooks. This greatly eases the conversion of data into machine-readable formats. As of this writing (Jan 2018), accessible versions are available only from 2008 through 2012. The complete Federal Sector Accounts tables from these Greenbooks and Tealbooks are available here in Excel format.
- These are simply cut and pasted from the published versions.
- Some have had blanks lines deleted to better align rows across different meetings.
- Each sheet contains the table from the FOMC meeting held in the month indicated by the sheet name.
- Greenbook Supplements never contained revisions to these tables. (There are no Tealbook Supplements.)
This is the code used to estimate the state-space models in Jacobs and van Norden (2011) Journal of Econometrics. It is far from easy to use (which is one of the reasons we’ve moved to use other code in subsequent research), but is posted here on a “as is” basis. The programs are in GAUSS and require the use of the TSM, the cmlmt and the TSAGAUSS applications. The latter is freely available while the others are copyrighted and available through Aptech (distributors of GAUSS.) cmlmt does constrained maximum-likelihood estimation, TSM does the Kalman filtering. However,
- While robust, TSM has not been updated since the early 90s (the version we used was distributed on 3.5″ diskettes) and lacks computational advances such as those described in Durbin and Koopman.
- The version of TSAGAUSS I have here is from 2001 (this is public software that I have nothing to do with so please don’t ask me about it.)
- Bayesian estimation has numerous advantages over maximum likelihood in richly-parameterized models
Code for Output Gaps
This is a collection of RATS and GAUSS programs and utilities, as well as the real-time real output data from the FRB Philadelphia.
Real-Time US Output Gaps
These are the gaps that were used in Orphanides and van Norden (2002) and Orphanides and van Norden (2005) and have been sporadically updated since. The main database is in RATS data format. There is also a data file in a text format (I think its an old TROLL format) in case you have trouble finding something to read RATS.
Real-Time Canadian Output Gaps
Code for switching regressions and Markov mixture models. The original documentation is van Norden and Vigfusson (1996) and the derivation of the analytic derivatives for Markov Switching Regressions was published in Gable, van Norden and Vigfusson (1997). The code was then extended somewhat for van Norden and Vigfusson (1998). It was originally designed to run in GAUSS 4.0. It should work fine under more recent versions of GAUSS, with the possible exception of the external C code (I’m not sure whether the GAUSS foreign language interface has since changed.)
The code has a few nice features;
- handles arbitrary numbers of explanatory variables in either regime.
- fast estimation of state-independent (i.e. simple switching) models with arbitrary numbers of explanatory variables in either regime.
- allows for time-varying Markovian transition probabilities with arbitrary numbers of explanatory variables in either regime.
- time-varying regime classification and transition probabilities with arbitrary numbers of explanatory variables in either regime.
- analytic derivatives
- external C-code for speed increase in Markov models (don’t know whether this still works.)
I wrote GAUSS code for the Hodrick Prescott filter early on when I started working on output gaps.