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Srikanth Ramamurthy

Personal Details

First Name:Srikanth
Middle Name:
Last Name:Ramamurthy
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RePEc Short-ID:pra537
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Affiliation

Department of Economics
Sellinger School of Business and Management
Loyola University of Maryland

Baltimore, Maryland (United States)
http://www.loyola.edu/sellinger/programs/economics/

(410) 617-2357


RePEc:edi:beloyus (more details at EDIRC)

Research output

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Jump to: Working papers Articles Chapters

Working papers

  1. Eric Gaus & Srikanth Ramamurthy, 2012. "Learning and Loss Functions: Comparing Optimal and Operational Monetary Policy Rules," Working Papers 14-01, Ursinus College, Department of Economics, revised 14 Dec 2013.
  2. Eric Gaus & Srikanth Ramamurthy, 2012. "Estimation of Constant Gain Learning Models," Working Papers 12-01, Ursinus College, Department of Economics, revised 01 Apr 2014.

Articles

  1. Srikanth Ramamurthy & Norman Sedgley, 2019. "A Note on School Quality, Educational Attainment and the Wage Gap," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 45(3), pages 415-421, June.
  2. Srikanth Ramamurthy & Norman Sedgley, 2015. "Human Capital Choice and the Wage Gap: The Role of Worklife Expectancy and Statistical Discrimination," Journal of Labor Research, Springer, vol. 36(2), pages 175-187, June.
  3. Siddhartha Chib & Srikanth Ramamurthy, 2014. "DSGE Models with Student- t Errors," Econometric Reviews, Taylor & Francis Journals, vol. 33(1-4), pages 152-171, June.
  4. Srikanth Ramamurthy & Norman Sedgley, 2013. "Exploring Fiscal Policy at Zero Interest Rates in Intermediate Macroeconomics," The Journal of Economic Education, Taylor & Francis Journals, vol. 44(4), pages 353-363, October.
  5. Chib, Siddhartha & Ramamurthy, Srikanth, 2010. "Tailored randomized block MCMC methods with application to DSGE models," Journal of Econometrics, Elsevier, vol. 155(1), pages 19-38, March.

Chapters

  1. Eric Gaus & Srikanth Ramamurthy, 2019. "A New Approach to Modeling Endogenous Gain Learning," Advances in Econometrics, in: Ivan Jeliazkov & Justin L. Tobias (ed.),Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part A, volume 40, pages 203-227, Emerald Publishing Ltd.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Eric Gaus & Srikanth Ramamurthy, 2012. "Estimation of Constant Gain Learning Models," Working Papers 12-01, Ursinus College, Department of Economics, revised 01 Apr 2014.

    Cited by:

    1. Michele Berardi & Jaqueson K Galimberti, 2016. "On the Initialization of Adaptive Learning in Macroeconomic Models," KOF Working papers 16-422, KOF Swiss Economic Institute, ETH Zurich.

Articles

  1. Siddhartha Chib & Srikanth Ramamurthy, 2014. "DSGE Models with Student- t Errors," Econometric Reviews, Taylor & Francis Journals, vol. 33(1-4), pages 152-171, June.

    Cited by:

    1. Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.
    2. Markku Lanne, 2013. "Noncausality and Inflation Persistence," Discussion Papers of DIW Berlin 1286, DIW Berlin, German Institute for Economic Research.
    3. Vasco Curdia & Marco Del Negro & Daniel L. Greenwald, 2012. "Rare shocks, great recessions," Staff Reports 585, Federal Reserve Bank of New York, revised 01 Jun 2013.
    4. Dave, Chetan & Malik, Samreen, 2017. "A tale of fat tails," European Economic Review, Elsevier, vol. 100(C), pages 293-317.
    5. Lindé, Jesper & Smets, Frank & Wouters, Rafael, 2016. "Challenges for Central Banks´ Macro Models," Working Paper Series 323, Sveriges Riksbank (Central Bank of Sweden).
    6. Chiu, Ching-Wai (Jeremy) & Mumtaz, Haroon & Pintér, Gábor, 2017. "Forecasting with VAR models: Fat tails and stochastic volatility," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1124-1143.
    7. Jonathan A. Attey & Casper G. de Vries, 2016. "Monetary Policy in the Presence of Random Wage Indexation," Tinbergen Institute Discussion Papers 16-086/VI, Tinbergen Institute.
    8. Marlène Isoré & Urszula Szczerbowicz, 2015. "Disaster Risk and Preference Shifts in a New Keynesian Model," Working Papers 2015-16, CEPII research center.
    9. Herwartz, Helmut & Lange, Alexander & Maxand, Simone, 2019. "Statistical identification in SVARs - Monte Carlo experiments and a comparative assessment of the role of economic uncertainties for the US business cycle," Center for European, Governance and Economic Development Research Discussion Papers 375, University of Goettingen, Department of Economics.
    10. Lindé, J. & Smets, F. & Wouters, R., 2016. "Challenges for Central Banks’ Macro Models," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.),Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 2185-2262, Elsevier.
    11. Liu, Xiaochun, 2019. "On tail fatness of macroeconomic dynamics," Journal of Macroeconomics, Elsevier, vol. 62(C).
    12. Ching-Wai (Jeremy) Chiu & Haroon Mumtaz & Gabor Pinter, 2016. "Bayesian Vector Autoregressions with Non-Gaussian Shocks," CReMFi Discussion Papers 5, CReMFi, School of Economics and Finance, QMUL.
    13. Mutschler, Willi, 2015. "Identification of DSGE models—The effect of higher-order approximation and pruning," Journal of Economic Dynamics and Control, Elsevier, vol. 56(C), pages 34-54.
    14. Michal Franta, 2015. "Rare Shocks vs. Non-linearities: What Drives Extreme Events in the Economy? Some Empirical Evidence," Working Papers 2015/04, Czech National Bank.
    15. Willi Mutschler, 2015. "Higher-order statistics for DSGE models," CQE Working Papers 4315, Center for Quantitative Economics (CQE), University of Muenster.
    16. Markus K. Brunnermeier & Darius Palia & Karthik A. Sastry & Christopher A. Sims, 2019. "Feedbacks: Financial Markets and Economic Activity," Working Papers 257, Princeton University, Department of Economics, Center for Economic Policy Studies..
    17. Ching-Wai (Jeremy) Chiu & Haroon Mumtaz & Gabor Pinter, 2014. "Fat-tails in VAR Models," Working Papers 714, Queen Mary University of London, School of Economics and Finance.
    18. Fabian Goessling, 2019. "Exact Expectations: Efficient Calculation of DSGE Models," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 977-990, March.
    19. Nelimarkka, Jaakko, 2017. "Evidence on News Shocks under Information Deficiency," MPRA Paper 80850, University Library of Munich, Germany.
    20. Puonti, Päivi, 2019. "Data-driven structural BVAR analysis of unconventional monetary policy," Journal of Macroeconomics, Elsevier, vol. 61(C), pages 1-1.
    21. Markku Lanne & Mika Meitz & Pentti Saikkonen, 2015. "Identification and estimation of non-Gaussian structural vector autoregressions," CREATES Research Papers 2015-16, Department of Economics and Business Economics, Aarhus University.
    22. Cross, Jamie & Poon, Aubrey, 2016. "Forecasting structural change and fat-tailed events in Australian macroeconomic variables," Economic Modelling, Elsevier, vol. 58(C), pages 34-51.

  2. Chib, Siddhartha & Ramamurthy, Srikanth, 2010. "Tailored randomized block MCMC methods with application to DSGE models," Journal of Econometrics, Elsevier, vol. 155(1), pages 19-38, March.

    Cited by:

    1. Masuhr Andreas & Trede Mark, 2020. "Bayesian estimation of generalized partition of unity copulas," Dependence Modeling, De Gruyter, vol. 8(1), pages 119-131, January.
    2. Mariano Kulish & James Morley & Tim Robinson, 2014. "Estimating DSGE models with forward guidance," Discussion Papers 2014-32A, School of Economics, The University of New South Wales.
    3. Negro, Marco Del & Schorfheide, Frank, 2013. "DSGE Model-Based Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.),Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 57-140, Elsevier.
    4. Dube, Arindrajit & Lester, T. William & Reich, Michael, 2011. "Do Frictions Matter in the Labor Market? Accessions, Separations and Minimum Wage Effects," IZA Discussion Papers 5811, Institute of Labor Economics (IZA).
    5. Paccagnini, Alessia, 2017. "Dealing with Misspecification in DSGE Models: A Survey," MPRA Paper 82914, University Library of Munich, Germany.
    6. Rey, Clément & Rey, Serge & Viala, Jean-Renaud, 2014. "Detection of high and low states in stock market returns with MCMC method in a Markov switching model," Economic Modelling, Elsevier, vol. 41(C), pages 145-155.
    7. Zheng, Tingguo & Guo, Huiming, 2013. "Estimating a small open economy DSGE model with indeterminacy: Evidence from China," Economic Modelling, Elsevier, vol. 31(C), pages 642-652.
    8. Edward P. Herbst & Frank Schorfheide, 2013. "Sequential Monte Carlo Sampling for DSGE Models," NBER Working Papers 19152, National Bureau of Economic Research, Inc.
    9. Benjamin Born & Johannes Pfeifer, 2013. "Policy Risk and the Business Cycle," CESifo Working Paper Series 4336, CESifo.
    10. Martin Burda & John M. Maheu, 2012. "Bayesian Adaptively Updated Hamiltonian Monte Carlo with an Application to High-Dimensional BEKK GARCH Models," Working Paper series 46_12, Rimini Centre for Economic Analysis.
    11. Rachael McCririck & Daniel Rees, 2016. "The Slowdown in US Productivity Growth: Breaks and Beliefs," RBA Research Discussion Papers rdp2016-08, Reserve Bank of Australia.
    12. Born, Benjamin & Peter, Alexandra & Pfeifer, Johannes, 2013. "Fiscal news and macroeconomic volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2582-2601.
    13. Wichitaksorn, Nuttanan & Tsurumi, Hiroki, 2013. "Comparison of MCMC algorithms for the estimation of Tobit model with non-normal error: The case of asymmetric Laplace distribution," Computational Statistics & Data Analysis, Elsevier, vol. 67(C), pages 226-235.
    14. Ricardo Reis & Vasco Curdia, 2009. "Correlated Disturbances and U.S. Business Cycles," 2009 Meeting Papers 129, Society for Economic Dynamics.
    15. Malley, James & Woitek, Ulrich, 2011. "Productivity shocks and aggregate fluctuations in an estimated endogenous growth model with human capital," SIRE Discussion Papers 2011-71, Scottish Institute for Research in Economics (SIRE).
    16. Fiorentini, G. & Planas, C. & Rossi, A., 2012. "The marginal likelihood of dynamic mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 56(9), pages 2650-2662.
    17. Fernández-Villaverde, J. & Rubio-Ramírez, J.F. & Schorfheide, F., 2016. "Solution and Estimation Methods for DSGE Models," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.),Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 527-724, Elsevier.
    18. Daniel O. Beltran & David Draper, 2018. "Estimating dynamic macroeconomic models: how informative are the data?," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(2), pages 501-520, February.
    19. Corbo, Vesna & Strid, Ingvar, 2020. "MAJA: A two-region DSGE model for Sweden and its main trading partners," Working Paper Series 391, Sveriges Riksbank (Central Bank of Sweden).
    20. Edward Herbst, 2012. "Using the \\"Chandrasekhar Recursions\\" for likelihood evaluation of DSGE models," Finance and Economics Discussion Series 2012-35, Board of Governors of the Federal Reserve System (U.S.), revised 2012.
    21. Brownstone, David & Li, Phillip, 2018. "A model for broad choice data," Journal of choice modelling, Elsevier, vol. 27(C), pages 19-36.
    22. Andreas Masuhr, 2019. "Big in Japan: Global Volatility Transmission between Assets and Trading Places," CQE Working Papers 8119, Center for Quantitative Economics (CQE), University of Muenster.
    23. Siddharta Chib & Minchul Shin & Anna Simoni, 2016. "Bayesian Empirical Likelihood Estimation and Comparison of Moment Condition Models," Working Papers 2016-21, Center for Research in Economics and Statistics.
    24. Markku Lanne & Jani Luoto, 2015. "Estimation of DSGE Models under Diffuse Priors and Data-Driven Identification Constraints," CREATES Research Papers 2015-37, Department of Economics and Business Economics, Aarhus University.
    25. Markku Lanne & Jani Luoto, 2014. "Noncausal Bayesian Vector Autoregression," CREATES Research Papers 2014-07, Department of Economics and Business Economics, Aarhus University.
    26. Peter Rosenkranz & Tobias Straumann & Ulrich Woitek, 2014. "A small open economy in the Great Depression: the case of Switzerland," ECON - Working Papers 164, Department of Economics - University of Zurich.
    27. Markku Lanne & Jani Luoto, 2018. "Data†Driven Identification Constraints for DSGE Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(2), pages 236-258, April.
    28. Dufays, A. & Rombouts, V., 2015. "Sparse Change-Point Time Series Models," CORE Discussion Papers 2015032, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    29. Michael T. Belongia & Peter N. Ireland, 2019. "A Reconsideration of Money Growth Rules," Boston College Working Papers in Economics 976, Boston College Department of Economics.
    30. Mariano Kulish & James Morley & Tim Robinson, 2016. "Estimating DSGE models with Zero Interest Rate Policy," Discussion Papers 2014-32B, School of Economics, The University of New South Wales.
    31. Mariano Kulish & James Morley & Tim Robinson, 2014. "Estimating the expected duration of the zero lower bound in DSGE models with forward guidance," Discussion Papers 2014-32, School of Economics, The University of New South Wales.
    32. Stelios D. Bekiros & Alessia Paccagnini, 2014. "Bayesian forecasting with small and medium scale factor-augmented vector autoregressive DSGE models," Open Access publications 10197/7322, School of Economics, University College Dublin.
    33. Ming Lin & Eric A. Suess & Robert H. Shumway & Rong Chen, 2016. "Bayesian Deconvolution of Signals Observed on Arrays," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(6), pages 837-850, November.
    34. Petrova, Katerina & Kapetanios, George & Masolo, Riccardo & Waldron, Matthew, 2017. "A time varying parameter structural model of the UK economy," Bank of England working papers 677, Bank of England.
    35. Li, Bing & Pei, Pei & Tan, Fei, 2018. "Credit Risk and Fiscal Inflation," MPRA Paper 90486, University Library of Munich, Germany.
    36. Edward Herbst, 2015. "Using the “Chandrasekhar Recursions” for Likelihood Evaluation of DSGE Models," Computational Economics, Springer;Society for Computational Economics, vol. 45(4), pages 693-705, April.
    37. Kazuhiko Kakamu & Haruhisa Nishino, 2019. "Bayesian Estimation of Beta-type Distribution Parameters Based on Grouped Data," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 625-645, August.
    38. DUFAYS, Arnaud, 2012. "Infinite-state Markov-switching for dynamic volatility and correlation models," CORE Discussion Papers 2012043, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    39. Iiboshi, Hirokuni & Shintani, Mototsugu, 2016. "Zero interest rate policy and asymmetric price adjustment in Japan: an empirical analysis of a nonlinear DSGE model," MPRA Paper 93868, University Library of Munich, Germany.
    40. Siddhartha Chib & Srikanth Ramamurthy, 2014. "DSGE Models with Student- t Errors," Econometric Reviews, Taylor & Francis Journals, vol. 33(1-4), pages 152-171, June.
    41. Jean-François Carpantier & Arnaud Dufays, 2014. "Specific Markov-switching behaviour for ARMA parameters," Working Papers hal-01821134, HAL.
    42. Andreas Masuhr, 2018. "Bayesian Estimation of Generalized Partition of Unity Copulas," CQE Working Papers 7318, Center for Quantitative Economics (CQE), University of Muenster.
    43. Mark Bognanni & Edward Herbst, 2014. "Estimating (Markov-Switching) VAR Models without Gibbs Sampling: A Sequential Monte Carlo Approach," Working Papers (Old Series) 1427, Federal Reserve Bank of Cleveland, revised 12 Nov 2014.
    44. Morris, Stephen D., 2017. "DSGE pileups," Journal of Economic Dynamics and Control, Elsevier, vol. 74(C), pages 56-86.
    45. Xin Luo & Håkon Tjelmeland, 2019. "A multiple-try Metropolis–Hastings algorithm with tailored proposals," Computational Statistics, Springer, vol. 34(3), pages 1109-1133, September.
    46. Young Min Kim & Seojin Lee, 2017. "The Role of Unobservable Fundamentals in Korea Exchange Rate Fluctuations: Bayesian Approach," Economic Analysis (Quarterly), Economic Research Institute, Bank of Korea, vol. 23(3), pages 1-22, September.
    47. Abdymomunov Azamat & Kang Kyu Ho, 2015. "The effects of monetary policy regime shifts on the term structure of interest rates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(2), pages 183-207, April.
    48. Kazuhiko Kakamu & Haruhisa Nishino, 2016. "Bayesian Estimation Of Beta-Type Distribution Parameters Based On Grouped Data," Discussion Papers 2016-08, Kobe University, Graduate School of Business Administration.
    49. Martin Burda & John Maheu, 2011. "Bayesian Adaptive Hamiltonian Monte Carlo with an Application to High-Dimensional BEKK GARCH Models," Working Papers tecipa-438, University of Toronto, Department of Economics.
    50. Jim Malley & Ulrich Woitek, 2019. "Estimated Human Capital Externalities in an Endogenous Growth Framework," Working Papers 2019_04, Business School - Economics, University of Glasgow.
    51. Bauwens, Luc & De Backer, Bruno & Dufays, Arnaud, 2014. "A Bayesian method of change-point estimation with recurrent regimes: Application to GARCH models," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 207-229.

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