Currency crisis: Evolution of beliefs and policy experiments

Arifovic, Jasmina; Maschek, Michael K.

doi:10.1016/j.jebo.2012.01.001

Cited by 7 publications

(4 citation statements)

References 10 publications

(10 reference statements)

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“…T he m ain m ethod in our research is agent-based com putational econom y (ACE) [13,29], w hich includes heterogeneity, bounded rationality, non-equilibrium dynam ics and direct interactions am ong econom ic agents [9]. A C E m odels are often used to study effects o f policies on m acroeconom ic and spatial dynam ics [4 ], and have already been im plem ented in different areas o f m acroeconom ic policy such as fiscal [2], m onetary [11,21], m acroprudential [1,3,19] and labor m arket policy [18,23,25].…”

Section: Literature Reviewmentioning

confidence: 99%

Simulating Budget System in the Agent Model of the Russian Federation Spatial Development

Mashkova

Novikova

Savina

et al. 2020

Communications in Computer and Information Science

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In this paper we present methods, data and algorithms for simulating budget system in the model of the Russian Federation spatial development. We show the place of this task in methodology of our research and give a brief overview of the background results. Key objects of the budget system in the model are the federal budget, regional budgets and extra budgetary funds: pension, medical and social insurance. We determine revenues and expenditures of the budgets and funds on the basis of federal laws, Budget and Tax codes of the Russian Federation. Since the exact reproduction of excise rates and customs duties is problematic due to model aggregation, we calculate model rates of excises and duties for selected sectors on the basis of retrospective data pre sented on the budget system portal and in the federal input-output table. Structure of the budget expenses in the model was simplified by aggregating expenditure items into major groups correlated with sectors of the economy. Presented algorithm of the budget system simulates interaction of the federal, regional budgets and extra-budgetary funds with agents and organizations in the model. For validation of the budget system algorithms in the model we conduct retrospective modeling for the federal budget and the budget of Belgorod region in 2014.

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Section: Literature Reviewmentioning

confidence: 99%

Simulating Budget System in the Agent Model of the Russian Federation Spatial Development

Mashkova

Novikova

Savina

et al. 2020

Communications in Computer and Information Science

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“…However, such expansionary policies raise inflation and lead to higher output volatility in the long-run. Arifovic and Maschek (2012) consider an open economy framework (see also Rengs and Wackerle, 2014), where a Central Bank fixes the interest rate in order to try to avoid the emergence of a currency crisis, which is triggered by the (heterogenous) devaluation expectations of investors, changing via a social evolutionary learning process. They find that decreasing the interest rates under the menace of a possible currency attack is more effective than defending the currency, as the latter policy increases the outflow of funds.…”

Section: Monetary Policymentioning

confidence: 99%

Macroeconomic Policy in DSGE and Agent-Based Models Redux: New Developments and Challenges Ahead

Fagiolo

Roventini

2016

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractThe Great Recession seems to be a natural experiment for economic analysis, in that it has shown the inadequacy of the predominant theoretical framework -the New Neoclassical Synthesis (NNS) -grounded on the DSGE model. In this paper, we present a critical discussion of the theoretical, empirical and political-economy pitfalls of the DSGE-based approach to policy analysis. We suggest that a more fruitful research avenue should escape the strong theoretical requirements of NNS models (e.g., equilibrium, rationality, representative agent, etc.) and consider the economy as a complex evolving system, i.e. as an ecology populated by heterogenous agents, whose far-from-equilibrium interactions continuously change the structure of the system. This is indeed the methodological core of agent-based computational economics (ACE), which is presented in this paper. We also discuss how ACE has been applied to policy analysis issues, and we provide a survey of macroeconomic policy applications (fiscal and monetary policy, bank regulation, labor market structural reforms and climate change interventions). Finally, we conclude by discussing the methodological status of ACE, as well as the problems it raises.

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“…Neural networks and genetic algorithms have proved to be quite efficient methods used to analyse financial (including currency) crisis episodes (Aydin & Cavdar, 2015;Sarlin, 2014;Arifovic & Maschek, 2012). Applying evolutionary algorithms allows to avoid suffering from some of the typical problems connected with working with financial data, such as volatility clustering or fat tails of the time series.…”

Section: Some Critical Points Towards Agent Behaviour In the Foreign mentioning

confidence: 99%

Using genetic algorithm in dynamic model of speculative attack

Gawrońska-Nowak

Grabowski

2016

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Evolution of speculative attack models shows certain progress in developing the idea of the role of expectations in the crisis mechanism. Obstfeld (1996) defines expectations as fully exogenous. Morris and Shin (1998) treat the expectations as endogenous (with respect to noise), not devoting too much attention to information structure of the foreign exchange market. Dynamic approach proposed by Angeletos, Hellwig and Pavan (2006) offers more sophisticated assumption about learning process. It tries to reflect time-variant and complex nature of information. However, this model ignores many important details like a Central Bank cost function. Genetic algorithm allows to avoid problems connected with incorporating information and expectations into agent decision-making process to an extent. There are some similarities between the evolution in Nature and currency market performance. In our paper an assumption about rational agent behaviour in the efficient market is criticised and we present our version of the dynamic model of a speculative attack, in which we use a genetic algorithm (GA) to define decision-making process of the currency market agents. The results of our simulation seem to be in line with the theory and intuition. An advantage of our model is that it reflects reality in a quite complex way, i.e. level of noise changes in time (decreasing), there are different states of fundamentals (with “more sensitive” upper part of the scale), the number of inflowing agents can be low or high (due to different globalization phases, different capital flow phases, different uncertainty levels).

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Currency crisis: Evolution of beliefs and policy experiments

Cited by 7 publications

References 10 publications

Simulating Budget System in the Agent Model of the Russian Federation Spatial Development

Simulating Budget System in the Agent Model of the Russian Federation Spatial Development

Macroeconomic Policy in DSGE and Agent-Based Models Redux: New Developments and Challenges Ahead

Using genetic algorithm in dynamic model of speculative attack

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