Economic Data

BigTex High-Performance Computing

About BigTex

As economic research becomes more data intensive and models become more complex, computing power is ever-more important. BigTex, provided by the Federal Reserve Bank of Dallas, is the largest high-performance computing (HPC) environment in the Federal Reserve System. It is used by Federal Reserve economists and their co-authors to investigate the big problems that only vast computing resources allow.

This research benefits Federal Reserve economists as well as researchers in academia and industry. Recent examples include research on the nonlinear impacts of the business cycle and monetary policy, algorithms that enable a researcher to update estimators using new data, and designing the best possible unemployment insurance payments during recessions and expansions. Check out the list of papers that were published as a result of using BigTex to learn more.

Access:

For further information about the environment or to request access, please email dal.bigtex.support@dal.frb.org.

Research

BigTex has opened the door to frontier economic research. The following is a list of working papers and publications in peer-reviewed academic journals that were supported in part through the computational resources provided by the BigTex high-performance computing environment.

“Shock-Dependent Exchange Rate Pass-Through: Evidence Based on a Narrative Sign Approach for Japan,” An, L., M. A. Wynne and R. Zhang, Journal of International Money and Finance, vol. 118, 2021, pp. 457-476. https://doi.org/10.1016/j.jeconom.2021.05.010.
“Job Applications and Labor Market Flows,” S. Birinci, K. See and S. L. Wee, Federal Reserve Bank of St. Louis Working Paper 2020-023, 2023. https://doi.org/10.20955/wp.2020.023.
“How To Go Viral: A COVID-19 Model with Endogenously Time-Varying Parameters,” P. Ho, T. A. Lubik and C. Matthes, Journal of Econometrics, vol. 232, 2023, pp. 70–86. https://doi.org/10.1016/j.jeconom.2021.01.001.
“Macroeconomic Forecasting and Variable Ordering in Multivariate Stochastic Volatility Models,” J. E. Arias, J. F. Rubio-Ramirez and M. Shin, Journal Econometrics, forthcoming. https://doi.org/10.1016/j.jeconom.2022.04.013.
“Labor Market Responses to Unemployment Insurance: The Role of Heterogeneity,” S. Birinci and K. See, American Economic Journal: Macroeconomics, Federal Reserve Bank of St. Louis Working Paper 2019-022, forthcoming. https://doi.org/10.20955/wp.2019.022.
“Global Robust Bayesian Analysis in Large Models,” P. Ho, Journal of Econometrics, forthcoming. https://doi.org/10.1016/j.jeconom.2022.06.004.
“The Distributional Effects of COVID-19 and Optimal Mitigation Policies,” S. Hur, International Economic Review, forthcoming. https://doi.org/10.24149/gwp400r4.
“Optimal Bailouts in Banking and Sovereign Crises,” S. Hur, C. Sosa-Padilla and Z. Yom, NBER Working Paper 28412, 2022. https://doi.org/10.3386/w28412.
“The Impact of Racial Segregation on College Attainment in Spatial Equilibrium,” V. Gregory, J. Kozlowski and H. Rubinton, Federal Reserve Bank of St. Louis Working Paper 2022-036A, 2022. https://doi.org/10.20955/wp.2022.036.
“Liquidity and Investment in General Equilibrium,” N. Caramp, J. Kozlowski and K. Teeple, Federal Reserve Bank of St. Louis Working Paper 2022-022B, 2022. https://doi.org/10.20955/wp.2022.022.
“Credit and Liquidity Policies During Large Crises,” M. Ebsim, M. F. E Castro and J. Kozlowski, Federal Reserve Bank of St. Louis Working Paper 2020-035, 2022. https://doi.org/10.20955/wp.2020.035.
“Beliefs, Aggregate Risk, and the U.S. Housing Boom,” M. M. Jacobson, Finance and Economics Discussion Series Working Paper 2022-061, 2022. https://doi.org/10.17016/FEDS.2022.061.
“Approximating Grouped Fixed Effects Estimation via Fuzzy Clustering Regression,” D. Lewis, D. Melcangi, L. Pilossoph and A. Toner-Rodgers, Federal Reserve Bank of New York Staff Reports 1033, 2022.
“Labor Market Shocks and Monetary Policy,” S. Birinci, F. Karahan, Y. Mercan and K. See, Federal Reserve Bank of St. Louis Working Paper 2022-016A, 2022. https://doi.org/10.20955/wp.2022.016.
“Valuation Risk Revalued,” O. De Groot, A. W. Richter and N. A. Throckmorton, Quantitative Economics, vol. 13, 2022, pp. 723–759. https://doi.org/10.3982/QE1779.
“Complementarity and Macroeconomic Uncertainty,” T. Atkinson, M. Plante, A. Richter and N. Throckmorton, Review of Economic Dynamics, vol. 44, 2022, pp. 225–243. https://doi.org/10.1016/j.red.2021.03.003.
“An Augmented Anderson-Hsiao Estimator for Dynamic Short-T Panels,” A. Chudik and M. H. Pesaran, Econometric Reviews, vol. 41, 2022, pp. 416–447. https://doi.org/10.1080/07474938.2021.1971388.
“Larger Transfers Financed with More Progressive Taxes? On the Optimal Design of Taxes and Transfers,” A. Ferriere, P. Grubener, G. Navarro and O. Vardishvili, CEPR Discussion Paper 16781, 2021.
“Shock-Dependent Exchange Rate Pass-Through: Evidence Based on a Narrative Sign Approach for Japan,” L. An, M. A. Wynne and R. Zhang, Journal of International Money and Finance, vol. 118, 2021. https://doi.org/10.1016/j.jimonfin.2021.102462.
“A Simple Explanation of Countercyclical Uncertainty,” J. Bernstein, M. Plante, A. Richter and N. Throckmorton, Federal Reserve Bank of Dallas Working Paper no. 2109, 2021. https://doi.org/10.24149/wp2109.
“Cyclical Net Entry and Exit,” J. Bernstein, A. W. Richter and N. A. Throckmorton, European Economic Review, vol. 136, 2021. https://doi.org/10.1016/j.euroecorev.2021.103752.
“Pooled Bewley Estimator of Long-Run Relationships in Dynamic Heterogenous Panels,” A. Chudik, M. H. Pesaran and R. P. Smith, Federal Reserve Bank of Dallas Globalization Institute Working Paper no. 409, 2021. https://doi.org/10.24149/gwp409.
“Variable Selection and Forecasting in High Dimensional Linear Regressions with Structural Breaks,” A. Chudik, M. H. Pesaran and M. Sharifvaghefi, Federal Reserve Bank of Dallas Globalization Institute Working Paper no. 394, 2021. https://doi.org/10.24149/gwp394r1.
“The Zero Lower Bound and Estimation Accuracy,” T. Atkinson, A. W. Richter and N. A. Throckmorton, Journal of Monetary Economics, vol. 115, 2020, pp. 249–264. https://doi.org/10.1016/j.jmoneco.2019.06.007.
“Online Estimation of DSGE Models,” M. Cai, M. Del, E. Herbst, E. Matlin, R. Sarfati and F. Schorfheide, Econometrics Journal, vol. 24, 2020, pp. 33–58. https://doi.org/10.1093/ectj/utaa029.
“The Heterogeneous Effects of Global and National Business Cycles on Employment in US States and Metropolitan Areas,” A. Chudik, J. Koech and M. Wynne, Oxford Bulletin of Economics and Statistics, vol. 83, 2020, pp. 495–517. https://doi.org/10.1111/obes.12402.