Consequently, we are building a collection of resources that researchers in this area may find useful.
Data: The MFM group cannot disseminate proprietary data; however we hope to become an online repository of datasets useful for replicating the research results of others. We encourage authors to share their data as far as licensing permits, and we will post such data on this website in data section below.
Software and Code: Below we provide key software and code that may be of interest to researchers.
Models: We have launched a model repository that can be found at: https://github.com/BFI-MFM
Real-Time Macroeconomic Data
Macroeconomic data are frequently revised by statistical agencies; this can complicate quantitative analysis, because it means researchers today may have better information about past conditions than policymakers at the time did. Croushore & Stark (2001) and Orphanides (2001) highlight the importance of using real-time data when analyzing macroeconomic policy and outcomes.
The Federal Reserve Bank of Philadelphia maintains a well-documented database of real-time macroeconomic data vintages, available for free on their website.
Official Macroeconomic Data Sources
Bank for International Settlements
The Bank for International Settlements (BIS) is an international organization of central banks that aims to increase cooperation and transparency among governments in the conduct of monetary policy. The BIS collects and disseminates a wide variety of international financial data, available here.
Bureau of Economic Analysis
The Bureau of Economic Analysis (BEA) tabulates data on U.S. output, personal income, and balance of payments. Their data are available for download here.
Bureau of Labor Statistics
The Bureau of Labor Statistics (BLS) collects and analyzes data on U.S. prices, unemployment, and working conditions. Their data are available for download here.
Congressional Budget Office
The Congressional Budget Office (CBO) produces independent analyses of budgetary and economic issues to support the Congressional budget process. The agency is strictly nonpartisan and conducts objective analyses. Their data are available here.
European Central Bank;
The European Central Bank (ECB) is responsible for conducting monetary policy for the euro area---the world’s largest economy after the United States. The ECB maintains a Statistical Data Warehouse on its website, available here.
Federal Reserve Board
The Federal Reserve Board (FRB) is the central governing body of the Federal Reserve System, which is responsible for conducting monetary policy in the U.S. The FRB collects and releases data on the U.S. Flow of Funds accounts, as well as various interest and exchange rates; their data are available here.
Office of Financial Research
The Office of Financial Research (OFR) is a department of the U.S. Treasury created by the Dodd-Frank Act to improve the quality of financial data and facilitate analyses of the financial system. Their data standards page is here.
Firm-Level Systemic Risk Measure (SRISK) computed by Acharya, Engle, & Richardson
Viral Acharya, Robert Engle, and Matthew Richardson propose a firm-level measure of the capital a firm would need to raise in the event of another financial crisis that was discussed at the 2012 meeting of the MFM group. Some of their data are available on the V-lab website.
Software and Code
In a live MATLAB script, we use MFM's toolbox (download here) to compute shock elasticities for Bansal and Yaron (2004). In the model, we transform two of the shocks to the macroeconomy in order that one is permanent and the other is transitory as in Hansen (2012). You can see how we perform the computations step by step, and the resulting plots illustrate that the recursive utility specification of investor preferences implies sizable compensations for the permanent shock even at short horizons in contrast to the power to the power utility model, in which the short-run compensations are small.
Jaroslav Borovicka, Lars Peter Hansen, and Jose Scheinkman construct shock elasticities which measure the contributions to the price and to the expected future cash flow from changes in the exposure to a shock in the next period. Currently there are two toolboxes based in MATLAB that compute shock elasticities. Jaroslav Borovicka's toolbox can be used for locally smooth models and MFM's toolbox can be applied to fundamentally nonlinear models.
Smolyak Method by Judd, Maliar, Maliar and Valero
Kenneth L. Judd, Lilia Maliar, Serguei Maliar and Rafael Valero show efficient implementation of the Smolyak method that avoids costly evaluations of repeated basis functions used in the conventional Smolyak formula. Also, the conventional Smolyak method is extended to include anisotropic constructions and an adaptive domain. The code is illustrated by simple examples and is portable to other applications. A MATLAB code of the Smolyak method is provided for download.
Epsilon distinguishable set (EDS) method and cluster grid algorithm (CGA) by Lilia Maliar and Serguei Maliar
Lilia Maliar and Serguei Maliar introduce epsilon distinguishable set (EDS) method and cluster grid algorithm (CGA) for solving dynamic economic models on the ergodic set and illustrate the application of the proposed methods in the context of one- and multi-sector dynamic stochastic general equilibrium (DSGE) models, Also, these methods are used to construct an accurate nonlinear solution to a medium-scale new Keynesian model with a zero lower bound on the nominal interest rate. The EDS and CGA codes are available for download.
Generalized Stochastic Simulation Algorithm by Judd, Maliar, & Maliar
Kenneth L. Judd, Lilia Maliar, and Serguei Maliar develop a numerical method to solve dynamic stochastic general equilibrium (DSGE) models with many state variables much faster than conventional methods allow. The method described in this paper is very similar to that presented by Serguei at the May 2013 meeting. MATLAB code implementing the algorithm is available for download.
Systemic Risk Measures surveyed by Bisias, Flood, Lo, & Valavanis
Dimitrios Bisias, Mark Flood, Andrew Lo, and Stavros Valavanis survey over thirty quantitative measures of systemic risk, which were discussed at the 2012 September meeting of the MFM group. MATLAB code and its documentation for implementing these measures can be downloaded here.
The Volatility Institute (V-Lab) provides real time measurement, modeling and forecasting of financial volatility, correlations and risk for a wide spectrum of assets. V-Lab blends together both classic models as well as some of the latest advances proposed in the financial econometrics literature. The aim of the website is to provide real time evidence on market dynamics for researchers, regulators, and practitioners.