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Books on the topic 'Stochastic cycle'

Author: Grafiati

Published: 9 March 2023

Last updated: 31 July 2025

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1

Jonsson, Gunnar. Stochastic fiscal policy and the Swedish business cycle. Stockholm University, Institute for International Economic Studies, 1995.

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2

Attfield, C. L. F. Stochastic trends and the business cycle in the UK. Bristol University, Department of Economics, 1992.

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3

Rotemberg, Julio. Is the business cycle a necessary consequence of stochastic growth? Alfred P. Sloan School of Management, Massachusetts Institute of Technology, 1994.

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4

Fernandez-Corugedo, Emilio. Imperfect information and the aggregate stochastic implications of the life cycle hypothesis. University of Bristol, Department of Economics, 1999.

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5

Lee, Danny C. The stochastic life-cycle model (SLCM): Simulating the population dynamics of anadromous salmonids. U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1992.

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6

B, Hyman Jeffrey, and Intermountain Research Station (Ogden, Utah), eds. The Stochastic Life-Cycle Model (SLCM): Simulating the population dynamics of anadromous salmonids. U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1992.

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7

B, Hyman Jeffrey, and Intermountain Research Station (Ogden, Utah), eds. The Stochastic Life-Cycle Model (SLCM): Simulating the population dynamics of anadromous salmonids. U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1992.

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8

Lee, Danny C. The stochastic life-cycle model (SLCM): Simulating the population dynamics of anadromous salmonids. U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1992.

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9

B, Hyman Jeffrey, and Intermountain Research Station (Ogden, Utah), eds. The Stochastic Life-Cycle Model (SLCM): Simulating the population dynamics of anadromous salmonids. U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1992.

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10

Pemberton, James. Attainable non-optimality or unattainable optimality: A new approach to stochastic life cycle problems. University of Reading, Dept. of Economics, 1992.

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11

Pemberton, James. Attainable non-optimality or unattainable optimality: A new approach to stochastic life cycle problems. University of Reading. Department of Economics, 1992.

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12

Dobrovolʹskiĭ, S. G. Anomalii globalʹnogo teplovlagoobmena: Stokhasticheskie modeli. Mezhduvedomstvennyĭ geofizicheskiĭ komitet pri Prezidiume AN SSSR, 1991.

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13

Shah, Janat. A stochastic programming with recourse model for supply chain and marketing planning of short life cycle products. Supply Chain Management Centre, Indian Institute of Management, 2008.

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14

Shah, Janat. A stochastic programming with recourse model for supply chain and marketing planning of short life cycle products. Supply Chain Management Centre, Indian Institute of Management, 2008.

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15

Taczanowski, Stefan. A preliminary concept of stochastic model of the tritium cycle in a fusion reactor =: Wstępny model stochastyczny cyklu trytowego w reaktorze termojądrowym. Institute of Physics and Nuclear Techniques, 1988.

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16

Grossman, Gene M. Quality ladders and product cycles. National Bureau of Economic Research, 1989.

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17

Aulin, Arvid. Causal and Stochastic Elements in Business Cycles. Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/978-3-642-95738-3.

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18

Gong, Gang. Stochastic dynamic macroeconomics: Theory, numerics, and empirical evidence. Oxford University Press, 2005.

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19

Gong, Gang. Stochastic dynamic macroeconomics: Theory and empirical evidence. Oxford University Press, 2004.

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20

Rotemberg, Julio. Stochastic technical progress, nearly smooth trends and distinct business cycles. National Bureau of Economic Research, 2002.

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21

Roche, Maurice J. Some linear-quadratic solution methods to stochastic nonlinear rational expectations models. Maynooth College, Department of Economics, 1994.

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22

Roche, Maurice J. Some linear-quadratic solution methods to stochastic nonlinear rational expectations models. Maynooth College, Department of Economics, 1994.

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23

Faig, Miquel. Booms and recessions in the basic neoclassical model: A stochastic analysis of technological shocks and fiscal policies. Dept. of Economics and Institute for Policy Analysis, University of Toronto, 1991.

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24

Aulin, Arvid. Causal and stochastic elements in business cycles: An essential extension of macroeconomics leading to improved predictions of data. Springer-Verlag, 1996.

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25

W, Evans George. Convergence of recursive learning mechanisms to steady states and cycles in stochastic nonlinear models. LSE Financial Markets Group, 1990.

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26

Corrado, Luisa. Reserves cycles and the collapse of the exchange rate mechanism: Deterministic and stochastic analysis. typescript, 1996.

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27

Stochastic Simulation of a Commander's Decision Cycle (SSIM Code). Storming Media, 2001.

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28

Rotemberg, Julio, and Michael Woodford. Is the Business Cycle a Necessary Consequence of Stochastic Growth? Creative Media Partners, LLC, 2018.

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29

Cycle Representations of Markov Processes (Stochastic Modelling and Applied Probability). Springer, 2006.

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30

Kalpazidou, Sophia L. Cycle Representations of Markov Processes (Stochastic Modelling and Applied Probability Book 28). Springer New York, 2007.

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31

The Stochastic Life-Cycle Model (SLCM): Simulating the population dynamics of anadromous salmonids. U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1992.

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32

A stochastic programming with recourse model for supply chain and marketing planning of short life cycle products. Supply Chain Management Centre, Indian Institute of Management, 2008.

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33

Wlaź, Paweł. Symulacje Monte Carlo. Teoria i zastosowania. Politechnika Lubelska, 2025. https://doi.org/10.35784/9788379476404.

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This academic script is based on notes from lectures and laboratories for the subject Monte Carlo Method, which is taught at the first‐cycle studies in the field of mathematics at the Lublin University of Techno‐ logy. The script discusses methods of generating pseudorandom sam‐ ples from various distributions, methods of measuring accuracy and reducing variance, calculations using the quasi‐Monte Carlo method, calculations related to stochastic processes and Metropolis–Hastings algorithm.

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34

Karmalita, Viacheslav. Stochastic Dynamics of Economic Cycles. de Gruyter GmbH, Walter, 2020.

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35

Karmalita, Viacheslav. Stochastic Dynamics of Economic Cycles. de Gruyter GmbH, Walter, 2020.

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36

Karmalita, Viacheslav. Stochastic Dynamics of Economic Cycles. de Gruyter GmbH, Walter, 2020.

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37

Cole, Harold L. Monetary and Fiscal Policy through a DSGE Lens. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190076030.001.0001.

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This text is designed to bridge the gap between Ph.D. and undergraduate textbooks in Macroeconomics. The text develops a dynamic stochastic general equilibrium model of money using a cash-in-advance constraint and endogenous production as in the real business cycle literature. The costs of inflation and optimal monetary policy, the impact of labor and capital taxes and as well as optimal fiscal policy are covered. Many extensions, including new Keynesian liquidity shock models are developed. Both standard analytic methods, such as Lagrangian methods, and computational methods using Matlab and

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38

Causal and Stochastic Elements in Business Cycles. Island Press, 1996.

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39

Semmier, Willi, and Gang Gong. Stochastic Dynamic Macroeconomics: Theory and Empirical Evidence. Oxford University Press, 2006.

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40

Gong, Gang, and Willi Semmler. Stochastic Dynamic Macroeconomics: Theory and Empirical Evidence. Oxford University Press, Incorporated, 2005.

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41

Holstein, Michael. Moderne Konjunkturtheorie: Reale Schocks, multiple Gleichgewichte und die Rolle der Geldpolitik (Hochschulschriften). Metropolis, 1998.

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42

Krolzig, H. International business cycles: Regime shifts in the stochastic process of economic growth. Oxford University, Institute of Economics and Statistics, 1997.

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43

Sosa, Marco Antonio Ortiz. Dynamic Stochastic General Equilibrium Models : Real Business Cycles Models: Closed and Open Economy. Springer, 2024.

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44

Aulin, Arvid. Causal and Stochastic Elements in Business Cycles: An Essential Extension of Macroeconomics Leading to Improved Predictions of Data. Springer London, Limited, 2012.

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45

Economic growth : theory and numerical solution methods. Springer, 2009.

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46

Aoki, Masanao. Modeling Aggregate Behavior and Fluctuations in Economics: Stochastic Views of Interacting Agents. Cambridge University Press, 2004.

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47

Aoki, Masanao. Modeling Aggregate Behavior and Fluctuations in Economics: Stochastic Views of Interacting Agents. Cambridge University Press, 2009.

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48

Aoki, Masanao. Modeling Aggregate Behavior and Fluctuations in Economics: Stochastic Views of Interacting Agents. Cambridge University Press, 2005.

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49

Aoki, Masanao. Modeling Aggregate Behavior and Fluctuations in Economics: Stochastic Views of Interacting Agents. Cambridge University Press, 2001.

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50

Quasi-Conservative Systems: Cycles, Resonances and Chaos. World Scientific Publishing Co Pte Ltd, 1998.

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