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Elizabeth Chase MacRae

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First Name:Elizabeth
Middle Name:Chase
Last Name:MacRae
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RePEc Short-ID:pma187

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Working papers

  1. Elizabeth Chase MacRae, 1972. "Optimal estimation and control: a structural approximation," Special Studies Papers 27, Board of Governors of the Federal Reserve System (U.S.).
  2. Elizabeth Chase MacRae, 1971. "Matrix derivatives with an application to the analysis of covariance structures," Special Studies Papers 20, Board of Governors of the Federal Reserve System (U.S.).

Articles

  1. Razavi, Hossein G. & MacRae, Elizabeth Chase, 1981. "Optimal stabilization policies for housing activity," Journal of Policy Modeling, Elsevier, vol. 3(1), pages 107-121, February.
  2. MacRae, Elizabeth Chase, 1977. "Estimation of Time-Varying Markov Processes with Aggregate Data," Econometrica, Econometric Society, vol. 45(1), pages 183-198, January.
  3. MacRae, C Duncan & MacRae, Elizabeth Chase, 1976. "Labor Supply and the Payroll Tax," American Economic Review, American Economic Association, vol. 66(3), pages 408-409, June.
  4. MacRae, Elizabeth Chase, 1975. "An Adaptive Learning Rule for Multiperiod Decision Problems," Econometrica, Econometric Society, vol. 43(5-6), pages 893-906, Sept.-Nov.

Chapters

  1. Elizabeth Chase MacRae, 1977. "Optimal Experimental Design for Dynamic Econometric Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 6, number 4, pages 399-405, National Bureau of Economic Research, Inc.
  2. Elizabeth Chase MacRae, 1972. "Linear Decision with Experimentation," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 1, number 4, pages 437-447, National Bureau of Economic Research, Inc.

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. Elizabeth Chase MacRae, 1972. "Optimal estimation and control: a structural approximation," Special Studies Papers 27, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Preston J. Miller & Arthur J. Rolnick, 1979. "The CBO's policy analysis: an unquestionable misuse of a questionable theory," Staff Report 49, Federal Reserve Bank of Minneapolis.
    2. Elizabeth Chase MacRae, 1972. "Linear Decision with Experimentation," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 1, number 4, pages 437-447, National Bureau of Economic Research, Inc.

  2. Elizabeth Chase MacRae, 1971. "Matrix derivatives with an application to the analysis of covariance structures," Special Studies Papers 20, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Elizabeth Chase MacRae, 1972. "Linear Decision with Experimentation," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 1, number 4, pages 437-447, National Bureau of Economic Research, Inc.

Articles

  1. MacRae, Elizabeth Chase, 1977. "Estimation of Time-Varying Markov Processes with Aggregate Data," Econometrica, Econometric Society, vol. 45(1), pages 183-198, January.

    Cited by:

    1. Jongeneel, Roelof A. & Longworth, Natasha & Huettel, Silke, 2005. "Dairy Farm Size Distribution in East and West: Evolution and Sensitivity to Structural and Policy Variables: Case-Studies of the Netherlands, Germany, Poland and Hungary," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24772, European Association of Agricultural Economists.
    2. Plantinga, Andrew J. & Ahn, Soeun, 2002. "Efficient Policies For Environmental Protection: An Econometric Analysis Of Incentives For Land Conversion And Retention," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 27(1), pages 1-18, July.
    3. Storm, Hugo & Heckelei, Thomas, 2011. "Bayesian estimation of non-stationary Markov models combining micro and macro data," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 103645, Agricultural and Applied Economics Association.
    4. Hua, Wei & Sohngen, Brent & Hite, Diane, 2005. "Assessing the Relationship Between Crop Choice and Land Use Change Using A Markov Model," 2005 Annual meeting, July 24-27, Providence, RI 19257, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    5. Karantininis, Kostas, 2001. "Information Based Estimators for the Non-Stationary Transition Probability Matrix: An Application to the Danish Pork Industry," Unit of Economics Working Papers 24198, Royal Veterinary and Agricultural University, Food and Resource Economic Institute.
    6. Jie Lin & Debbie A. Niemeier, 2003. "Estimating Regional Air Quality Vehicle Emission Inventories: Constructing Robust Driving Cycles," Transportation Science, INFORMS, vol. 37(3), pages 330-346, August.
    7. Pasanisi, Alberto & Fu, Shuai & Bousquet, Nicolas, 2012. "Estimating discrete Markov models from various incomplete data schemes," Computational Statistics & Data Analysis, Elsevier, vol. 56(9), pages 2609-2625.
    8. Pedauga, Luis & Pineda, Julio & Miguel, Dorta, 2004. "Rivalidad por clientes en el mercado cambiario venezolano [Rivalry for customers in the Venezuelan exchange market]," MPRA Paper 62431, University Library of Munich, Germany.
    9. Saint-Cyr, Legrand D.F. & Piet, Laurent, 2015. "Movers and Stayers in the Farming Sector: Accounting for Unobserved Heterogeneity in Structural Change," 89th Annual Conference, April 13-15, 2015, Warwick University, Coventry, UK 204234, Agricultural Economics Society.
    10. Legrand D. F, Saint-Cyr, 2017. "Farm heterogeneity and agricultural policy impacts on size dynamics: evidence from France," Working Papers SMART 17-04, INRAE UMR SMART.
    11. Huettel, Silke & Jongeneel, Roelof A., 2009. "Impact of the EU Milk Quota on Structural Change in the Dairy Sectors of Germany and The Netherlands," 2009 Conference, August 16-22, 2009, Beijing, China 50943, International Association of Agricultural Economists.
    12. Ben Ayara, Amine & Cho, Seong-Hoon & Clark, Christopher & Lambert, Dayton & Armsworth, Paul, 2016. "Spatial and Temporal Variation in the Optimal Provision of Forest-based Carbon Storage," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236005, Agricultural and Applied Economics Association.
    13. Zimmermann, Andrea & Heckelei, Thomas, 2012. "Differences of farm structural change across European regions," Discussion Papers 162879, University of Bonn, Institute for Food and Resource Economics.
    14. Arie ten Cate, 2014. "Maximum likelihood estimation of the Markov chain model with macro data and the ecological inference model," CPB Discussion Paper 284, CPB Netherlands Bureau for Economic Policy Analysis.
    15. Davor Kunovac, 2011. "Estimating Credit Migration Matrices with Aggregate Data – Bayesian Approach," Working Papers 30, The Croatian National Bank, Croatia.
    16. Jeffrey M. Gillespie & Joan R. Fulton, 2001. "A Markov chain analysis of the size of hog production firms in the United States," Agribusiness, John Wiley & Sons, Ltd., vol. 17(4), pages 557-570.
    17. Coppejans, Mark & Domowitz, Ian, 1999. "Pricing behavior in an off-hours computerized market," Journal of Empirical Finance, Elsevier, vol. 6(5), pages 583-607, December.
    18. Richard F. Kosobud & Houston H. Stokes, 1980. "Simulation of World Oil Market Shocks: A Markov Analysis of OPEC and Consumer Behavior," The Energy Journal, , vol. 1(2), pages 55-84, April.
    19. Melanie Parravano & Luis Enrique Pedauga, 2008. "Oil market dynamics: A Markow chain analysis," Economía, Instituto de Investigaciones Económicas y Sociales (IIES). Facultad de Ciencias Económicas y Sociales. Universidad de Los Andes. Mérida, Venezuela, vol. 33(25), pages 87-115, january-j.
    20. Mr. Matthew T Jones, 2005. "Estimating Markov Transition Matrices Using Proportions Data: An Application to Credit Risk," IMF Working Papers 2005/219, International Monetary Fund.
    21. Zepeda, Lydia & Chavas, Jean-Paul, 1991. "The Structure of Wisconsin Milk production: a Dynamic Analysis," WAEA/ WFEA Conference Archive (1929-1995) 321485, Western Agricultural Economics Association.
    22. Jacob Fiksel & Scott Zeger & Abhirup Datta, 2022. "A transformation‐free linear regression for compositional outcomes and predictors," Biometrics, The International Biometric Society, vol. 78(3), pages 974-987, September.
    23. Christina M. L. Kelton, 1984. "Nonstationary Markov Modeling: An Application to Wage-Influenced Industrial Relocation," International Regional Science Review, , vol. 9(1), pages 75-90, September.
    24. Douglas J. Miller & George Judge, 2015. "Information Recovery in a Dynamic Statistical Markov Model," Econometrics, MDPI, vol. 3(2), pages 1-12, March.
    25. Enrico Fabrizi & Gianni Guastella & Stefano Marta & Francesco Timpano, 2016. "Determinants of Intra-Distribution Dynamics in European Regions: An Empirical Assessment of the Role of Structural Intervention," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 107(5), pages 522-539, December.
    26. Felteau, Claude & Lefebvre, Pierre & Merrigan, Philip & Brouillette, Liliane, 1997. "Conjugalité et fécondité des femmes canadiennes : un modèle dynamique estimé à l’aide d’une série de coupes transversales," L'Actualité Economique, Société Canadienne de Science Economique, vol. 73(1), pages 233-263, mars-juin.
    27. Jongeneel, Roelof A., 2002. "An Analysis of the Impact of Alternative EU Dairy Policies on the Size Distribution of Dutch Dairy Farms: an Information Based Approach to the Non-Stationary Markov Chain Model," 2002 International Congress, August 28-31, 2002, Zaragoza, Spain 24892, European Association of Agricultural Economists.
    28. Karol Flisikowski & Dagmara Nikulin, 2015. "Workforce Mobility Against The Background Of Labour Market Duality Theory – The Example Of Selected Oecd Countries," GUT FME Conference Publications, in: Katarzyna Stankiewicz (ed.),Contemporary Issues and Challenges in Human Resource Management, chapter 2, pages 9-17, Faculty of Management and Economics, Gdansk University of Technology.
    29. Silke Huettel & Anne Margarian, 2009. "Structural change in the West German agricultural sector," Agricultural Economics, International Association of Agricultural Economists, vol. 40(s1), pages 759-772, November.
    30. D. M. Lambert & C. N. Boyer & L. He, 2016. "Spatial-temporal heteroskedastic robust covariance estimation for Markov transition probabilities: an application examining land use change," Letters in Spatial and Resource Sciences, Springer, vol. 9(3), pages 353-362, October.
    31. Arkadiusz Manikowski, 2021. "The Markov Process as a Model of Migration Based on the Example of the Movement of Banknotes (Proces Markowa jako model migracji na przykladzie przemieszczania sie banknotow)," Research Reports, University of Warsaw, Faculty of Management, vol. 2(35), pages 76-92.
    32. Barsotti, Flavia & De Castro, Yohann & Espinasse, Thibault & Rochet, Paul, 2014. "Estimating the transition matrix of a Markov chain observed at random times," Statistics & Probability Letters, Elsevier, vol. 94(C), pages 98-105.
    33. Saint-Cyr, Legrand D. F. & Piet, Laurent, 2014. "Movers and Stayers in the Farming Sector: Another Look at Heterogeneity in Structural Change," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 183068, European Association of Agricultural Economists.
    34. Love, H. Alan & Karp, Larry, 1988. "The Effect of Anticipated Farm Failure on the.Agricultural Land Market," 1988 Annual Meeting, August 1-3, Knoxville, Tennessee 270186, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    35. Bernard Fingleton, 1999. "Estimates of Time to Economic Convergence: An Analysis of Regions of the European Union," International Regional Science Review, , vol. 22(1), pages 5-34, April.

  2. MacRae, Elizabeth Chase, 1975. "An Adaptive Learning Rule for Multiperiod Decision Problems," Econometrica, Econometric Society, vol. 43(5-6), pages 893-906, Sept.-Nov.

    Cited by:

    1. Tucci, Marco P. & Kendrick, David A. & Amman, Hans M., 2010. "The parameter set in an adaptive control Monte Carlo experiment: Some considerations," Journal of Economic Dynamics and Control, Elsevier, vol. 34(9), pages 1531-1549, September.
    2. King, Robert P., 1979. "Operational Techniques for Applied Decision Analysis Under Uncertainty," AAEA Fellows - Dissertations and Theses, Agricultural and Applied Economics Association, number 181951, December.
    3. D.A. Kendrick & H.M. Amman & M.P. Tucci, 2008. "Learning About Learning in Dynamic Economic Models," Working Papers 08-20, Utrecht School of Economics.
    4. Hans M. Amman & Marco P. Tucci, 2020. "How Active is Active Learning: Value Function Method Versus an Approximation Method," Computational Economics, Springer;Society for Computational Economics, vol. 56(3), pages 675-693, October.
    5. Hans M. Amman & David A. Kendrick, 2003. "A Classification System for Economic Stochastic Control Models," Computing in Economics and Finance 2003 114, Society for Computational Economics.
    6. David Kendrick, 1976. "Applications of Control Theory to Macroeconomics," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 2, pages 171-190, National Bureau of Economic Research, Inc.
    7. Marco Tucci & David Kendrick & Hans Amman, 2013. "Expected Optimal Feedback with Time-Varying Parameters," Computational Economics, Springer;Society for Computational Economics, vol. 42(3), pages 351-371, October.
    8. Johnson, Timothy C., 2007. "Optimal learning and new technology bubbles," Journal of Monetary Economics, Elsevier, vol. 54(8), pages 2486-2511, November.
    9. D. Blueschke & V. Blueschke-Nikolaeva & R. Neck, 2013. "Stochastic Control of Linear and Nonlinear Econometric Models: Some Computational Aspects," Computational Economics, Springer;Society for Computational Economics, vol. 42(1), pages 107-118, June.
    10. Hans M. Amman & Marco Paolo Tucci, 2018. "How active is active learning: value function method vs an approximation method," Department of Economics University of Siena 788, Department of Economics, University of Siena.
    11. Kendrick, David A., 2005. "Stochastic control for economic models: past, present and the paths ahead," Journal of Economic Dynamics and Control, Elsevier, vol. 29(1-2), pages 3-30, January.
    12. H.M. Amman & D.A. Kendrick, 2012. "Conjectures on the policy function in the presence of optimal experimentation," Working Papers 12-09, Utrecht School of Economics.
    13. Ivan Savin & Dmitri Blueschke, 2016. "Lost in Translation: Explicitly Solving Nonlinear Stochastic Optimal Control Problems Using the Median Objective Value," Computational Economics, Springer;Society for Computational Economics, vol. 48(2), pages 317-338, August.
    14. Cosimano, Thomas F., 2008. "Optimal experimentation and the perturbation method in the neighborhood of the augmented linear regulator problem," Journal of Economic Dynamics and Control, Elsevier, vol. 32(6), pages 1857-1894, June.
    15. Amman, Hans M. & Kendrick, David A. & Tucci, Marco P., 2020. "Approximating The Value Function For Optimal Experimentation," Macroeconomic Dynamics, Cambridge University Press, vol. 24(5), pages 1073-1086, July.
    16. Ivan Savin & Dmitri Blueschke, 2013. "Solving nonlinear stochastic optimal control problems using evolutionary heuristic optimization," Jena Economics Research Papers 2013-051, Friedrich-Schiller-University Jena.

Chapters

  1. Elizabeth Chase MacRae, 1977. "Optimal Experimental Design for Dynamic Econometric Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 6, number 4, pages 399-405, National Bureau of Economic Research, Inc.

    Cited by:

    1. Rausser, Gordon & Mundlak, Yair & Johnson, S.R., 1981. "Structural Change, Updating, and Forecasting," CUDARE Working Papers 198213, University of California, Berkeley, Department of Agricultural and Resource Economics.

  2. Elizabeth Chase MacRae, 1972. "Linear Decision with Experimentation," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 1, number 4, pages 437-447, National Bureau of Economic Research, Inc.

    Cited by:

    1. Tucci, Marco P. & Kendrick, David A. & Amman, Hans M., 2010. "The parameter set in an adaptive control Monte Carlo experiment: Some considerations," Journal of Economic Dynamics and Control, Elsevier, vol. 34(9), pages 1531-1549, September.
    2. D.A. Kendrick & H.M. Amman & M.P. Tucci, 2008. "Learning About Learning in Dynamic Economic Models," Working Papers 08-20, Utrecht School of Economics.
    3. Hans M. Amman & Marco P. Tucci, 2020. "How Active is Active Learning: Value Function Method Versus an Approximation Method," Computational Economics, Springer;Society for Computational Economics, vol. 56(3), pages 675-693, October.
    4. Hans M. Amman & David A. Kendrick, 2003. "A Classification System for Economic Stochastic Control Models," Computing in Economics and Finance 2003 114, Society for Computational Economics.
    5. David Kendrick, 1976. "Applications of Control Theory to Macroeconomics," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 2, pages 171-190, National Bureau of Economic Research, Inc.
    6. Marco Tucci & David Kendrick & Hans Amman, 2013. "Expected Optimal Feedback with Time-Varying Parameters," Computational Economics, Springer;Society for Computational Economics, vol. 42(3), pages 351-371, October.
    7. Yaakov Bar-Shalom & Edison Tse, 1976. "Caution, Probing, and the Value of Information in the Control of Uncertain Systems," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 3, pages 323-337, National Bureau of Economic Research, Inc.
    8. Chee-Yee Chong & David Cheng, 1975. "Multistage Pricing under Uncertain Demand," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 4, number 2, pages 311-323, National Bureau of Economic Research, Inc.
    9. In Chang Hwang & Richard S. J. Tol & Marjan W. Hofkes, 2019. "Active Learning and Optimal Climate Policy," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 73(4), pages 1237-1264, August.
    10. Hans M. Amman & Marco Paolo Tucci, 2018. "How active is active learning: value function method vs an approximation method," Department of Economics University of Siena 788, Department of Economics, University of Siena.
    11. Marco Paolo Tucci, 2019. "The usual robust control framework in discrete time: Some interesting results," Department of Economics University of Siena 815, Department of Economics, University of Siena.
    12. Kendrick, David A., 2005. "Stochastic control for economic models: past, present and the paths ahead," Journal of Economic Dynamics and Control, Elsevier, vol. 29(1-2), pages 3-30, January.
    13. H.M. Amman & D.A. Kendrick, 2012. "Conjectures on the policy function in the presence of optimal experimentation," Working Papers 12-09, Utrecht School of Economics.
    14. Tim Willems, 2017. "Actively Learning by Pricing: A Model of an Experimenting Seller," Economic Journal, Royal Economic Society, vol. 127(604), pages 2216-2239, September.
    15. Tucci, Marco P., 2002. "A note on global optimization in adaptive control, econometrics and macroeconomics," Journal of Economic Dynamics and Control, Elsevier, vol. 26(9-10), pages 1739-1764, August.
    16. Cosimano, Thomas F., 2008. "Optimal experimentation and the perturbation method in the neighborhood of the augmented linear regulator problem," Journal of Economic Dynamics and Control, Elsevier, vol. 32(6), pages 1857-1894, June.
    17. Marco P. Tucci, 2024. "A Critical Introduction to the Usual Robust Control Framework in Macroeconomics," Computational Economics, Springer;Society for Computational Economics, vol. 64(2), pages 625-641, August.
    18. Sweder van Wijnbergen & Tim Willems, 2012. "Optimal Learning on Climate Change: Why Climate Skeptics should reduce Emissions," Tinbergen Institute Discussion Papers 12-085/2, Tinbergen Institute.
    19. Tucci, Marco P., 1997. "Adaptive control in the presence of time-varying parameters," Journal of Economic Dynamics and Control, Elsevier, vol. 22(1), pages 39-47, November.
    20. Amman, Hans M. & Kendrick, David A. & Tucci, Marco P., 2020. "Approximating The Value Function For Optimal Experimentation," Macroeconomic Dynamics, Cambridge University Press, vol. 24(5), pages 1073-1086, July.
    21. Alfred L. Norman, 1976. "First Order Dual Control," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 3, pages 311-321, National Bureau of Economic Research, Inc.
    22. In Chang Hwang, 2016. "Active learning and optimal climate policy," EcoMod2016 9611, EcoMod.
    23. V. Blueschke-Nikolaeva & D. Blueschke & R. Neck, 2020. "OPTCON3: An Active Learning Control Algorithm for Nonlinear Quadratic Stochastic Problems," Computational Economics, Springer;Society for Computational Economics, vol. 56(1), pages 145-162, June.
    24. Beck, Gunter W. & Wieland, Volker, 2002. "Learning and control in a changing economic environment," Journal of Economic Dynamics and Control, Elsevier, vol. 26(9-10), pages 1359-1377, August.
    25. Marco Tucci, 2006. "Understanding the Difference Between Robust Control and Optimal Control in a Linear Discrete-Time System with Time-Varying Parameters," Computational Economics, Springer;Society for Computational Economics, vol. 27(4), pages 533-558, June.

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