179 resultados para Probabilistic Models


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Working Paper no longer available. Please contact the author.

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In this work I study the stability of the dynamics generated by adaptivelearning processes in intertemporal economies with lagged variables. Iprove that determinacy of the steady state is a necessary condition for the convergence of the learning dynamics and I show that the reciprocal is not true characterizing the economies where convergence holds. In the case of existence of cycles I show that there is not, in general, a relationship between determinacy and convergence of the learning process to the cycle. I also analyze the expectational stability of these equilibria.

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This paper explores three aspects of strategic uncertainty: its relation to risk, predictability of behavior and subjective beliefs of players. In a laboratory experiment we measure subjects certainty equivalents for three coordination games and one lottery. Behavior in coordination games is related to risk aversion, experience seeking, and age.From the distribution of certainty equivalents we estimate probabilities for successful coordination in a wide range of games. For many games, success of coordination is predictable with a reasonable error rate. The best response to observed behavior is close to the global-game solution. Comparing choices in coordination games with revealed risk aversion, we estimate subjective probabilities for successful coordination. In games with a low coordination requirement, most subjects underestimate the probability of success. In games with a high coordination requirement, most subjects overestimate this probability. Estimating probabilistic decision models, we show that the quality of predictions can be improved when individual characteristics are taken into account. Subjects behavior is consistent with probabilistic beliefs about the aggregate outcome, but inconsistent with probabilistic beliefs about individual behavior.

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We examine the effects of extracting monetary policy disturbances with semi-structural and structural VARs, using data generated bya limited participation model under partial accommodative and feedback rules. We find that, in general, misspecification is substantial: short run coefficients often have wrong signs; impulse responses and variance decompositions give misleadingrepresentations of the dynamics. Explanations for the results and suggestions for macroeconomic practice are provided.

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We investigate identifiability issues in DSGE models and their consequences for parameter estimation and model evaluation when the objective function measures the distance between estimated and model impulse responses. We show that observational equivalence, partial and weak identification problems are widespread, that they lead to biased estimates, unreliable t-statistics and may induce investigators to select false models. We examine whether different objective functions affect identification and study how small samples interact with parameters and shock identification. We provide diagnostics and tests to detect identification failures and apply them to a state-of-the-art model.

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This Article breaks new ground toward contractual and institutional innovation in models of homeownership, equity building, and mortgage enforcement. Inspired by recent developments in the affordable housing sector and other types of public financing schemes, we suggest extending institutional and financial strategies such as time- and place-based division of property rights, conditional subsidies, and credit mediation to alleviate the systemic risks of mortgage foreclosure. Two new solutions offer a broad theoretical basis for such developments in the economic and legal institution of homeownership: a for-profit shared equity scheme led by local governments alongside a private market shared equity model, one of "bootstrapping home buying with purchase options".

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We see that the price of an european call option in a stochastic volatilityframework can be decomposed in the sum of four terms, which identifythe main features of the market that affect to option prices: the expectedfuture volatility, the correlation between the volatility and the noisedriving the stock prices, the market price of volatility risk and thedifference of the expected future volatility at different times. We alsostudy some applications of this decomposition.

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This chapter highlights the problems that structural methods and SVAR approaches have when estimating DSGE models and examining their ability to capture important features of the data. We show that structural methods are subject to severe identification problems due, in large part, to the nature of DSGE models. The problems can be patched up in a number of ways but solved only if DSGEs are completely reparametrized or respecified. The potential misspecification of the structural relationships give Bayesian methods an hedge over classical ones in structural estimation. SVAR approaches may face invertibility problems but simple diagnostics can help to detect and remedy these problems. A pragmatic empirical approach ought to use the flexibility of SVARs against potential misspecificationof the structural relationships but must firmly tie SVARs to the class of DSGE models which could have have generated the data.

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Since ethical concerns are calling for more attention within OperationalResearch, we present three approaches to combine Operational Researchmodels with ethics. Our intention is to clarify the trade-offs faced bythe OR community, in particular the tension between the scientificlegitimacy of OR models (ethics outside OR models) and the integrationof ethics within models (ethics within OR models). Presenting anddiscussing an approach that combines OR models with the process of OR(ethics beyond OR models), we suggest rigorous ways to express the relationbetween ethics and OR models. As our work is exploratory, we are trying toavoid a dogmatic attitude and call for further research. We argue thatthere are interesting avenues for research at the theoretical,methodological and applied levels and that the OR community can contributeto an innovative, constructive and responsible social dialogue about itsethics.

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Why was England first? And why Europe? We present a probabilistic model that builds on big-push models by Murphy, Shleifer and Vishny (1989), combined with hierarchical preferences. The interaction of exogenous demographic factors (in particular the English low-pressure variant of the European marriage pattern)and redistributive institutions such as the old Poor Law combined to make an Industrial Revolution more likely. Essentially, industrialization is the result of having a critical mass of consumers that is rich enough to afford (potentially) mass-produced goods. Our model is then calibrated to match the main characteristics of the English economy in 1750 and the observed transition until 1850.This allows us to address explicitly one of the key features of the British IndustrialRevolution unearthed by economic historians over the last three decades the slowness of productivity and output change. In our calibration, we find that the probability of Britain industrializing is 5 times larger than France s. Contrary to the recent argument by Pomeranz, China in the 18th century had essentially no chance to industrialize at all. This difference is decomposed into a demographic and a policy component, with the former being far more important than the latter.

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This paper describes a methodology to estimate the coefficients, to test specification hypothesesand to conduct policy exercises in multi-country VAR models with cross unit interdependencies, unit specific dynamics and time variations in the coefficients. The framework of analysis is Bayesian: a prior flexibly reduces the dimensionality of the model and puts structure on the time variations; MCMC methods are used to obtain posterior distributions; and marginal likelihoods to check the fit of various specifications. Impulse responses and conditional forecasts are obtained with the output of MCMC routine. The transmission of certain shocks across countries is analyzed.

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We analyze the role of commitment in pre-play communication for ensuringefficient evolutionarily stable outcomes in coordination games. All players are a priori identical as they are drawn from the same population. In games where efficient outcomes can be reached by players coordinating on the same action we find commitment to be necessary to enforce efficiency. In games where efficienct outcomes only result from play of different actions, communication without commitment is most effective although efficiency can no longer be guaranteed. Only when there are many messages then inefficient outcomes are negligible as their basins of attraction become very small.

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This paper illustrates the philosophy which forms the basis of calibrationexercises in general equilibrium macroeconomic models and the details of theprocedure, the advantages and the disadvantages of the approach, with particularreference to the issue of testing ``false'' economic models. We provide anoverview of the most recent simulation--based approaches to the testing problemand compare them to standard econometric methods used to test the fit of non--lineardynamic general equilibrium models. We illustrate how simulation--based techniques can be used to formally evaluate the fit of a calibrated modelto the data and obtain ideas on how to improve the model design using a standardproblem in the international real business cycle literature, i.e. whether amodel with complete financial markets and no restrictions to capital mobility is able to reproduce the second order properties of aggregate savingand aggregate investment in an open economy.

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The past four decades have witnessed an explosive growth in the field of networkbased facilitylocation modeling. This is not at all surprising since location policy is one of the mostprofitable areas of applied systems analysis in regional science and ample theoretical andapplied challenges are offered. Location-allocation models seek the location of facilitiesand/or services (e.g., schools, hospitals, and warehouses) so as to optimize one or severalobjectives generally related to the efficiency of the system or to the allocation of resources.This paper concerns the location of facilities or services in discrete space or networks, thatare related to the public sector, such as emergency services (ambulances, fire stations, andpolice units), school systems and postal facilities. The paper is structured as follows: first,we will focus on public facility location models that use some type of coverage criterion,with special emphasis in emergency services. The second section will examine models based onthe P-Median problem and some of the issues faced by planners when implementing thisformulation in real world locational decisions. Finally, the last section will examine newtrends in public sector facility location modeling.