A Higher order and stable method for the numerical integration of Random Differential Equations

Trabalho apresentado no Congresso Nacional de Matemática Aplicada à Indústria, 18 a 21 de novembro de 2014, Caldas Novas - Goiás

A family of autoregressive conditional duration models

This paper develops a family of autoregressive conditional duration (ACD) models that encompasses most specifications in the literature. The nesting relies on a Box-Cox transformation with shape parameter λ to the conditional duration process and a possibly asymmetric shocks impact curve. We establish conditions for the existence of higher-order moments, strict stationarity, geometric ergodicity and β-mixing property with exponential decay. We next derive moment recursion relations and the autocovariance function of the power λ of the duration process. Finally, we assess the practical usefulness of our family of ACD models using NYSE transactions data, with special attention to IBM price durations. The results warrant the extra flexibility provided either by the Box-Cox transformation or by the asymmetric response to shocks.

A family of autoregressive conditional duration models

This paper develops a family of autoregressive conditional duration (ACD) models that encompasses most specifications in the literature. The nesting relies on a Box-Cox transformation with shape parameter λ to the conditional duration process and a possibly asymmetric shocks impact curve. We establish conditions for the existence of higher-order moments, strict stationarity, geometric ergodicity and β-mixing property with exponential decay. We next derive moment recursion relations and the autocovariance function of the power λ of the duration process. Finally, we assess the practical usefulness of our family of ACD models using NYSE price duration data on the IBM stock. The results warrant the extra flexibility provided either by the Box-Cox transformation or by the asymmetric response to shocks.

Testing the optimality of aggregate consumption decisions: is there rule-of-thumb behavior?

Consumption is an important macroeconomic aggregate, being about 70% of GNP. Finding sub-optimal behavior in consumption decisions casts a serious doubt on whether optimizing behavior is applicable on an economy-wide scale, which, in turn, challenge whether it is applicable at all. This paper has several contributions to the literature on consumption optimality. First, we provide a new result on the basic rule-of-thumb regression, showing that it is observational equivalent to the one obtained in a well known optimizing real-business-cycle model. Second, for rule-of-thumb tests based on the Asset-Pricing Equation, we show that the omission of the higher-order term in the log-linear approximation yields inconsistent estimates when lagged observables are used as instruments. However, these are exactly the instruments that have been traditionally used in this literature. Third, we show that nonlinear estimation of a system of N Asset-Pricing Equations can be done efficiently even if the number of asset returns (N) is high vis-a-vis the number of time-series observations (T). We argue that efficiency can be restored by aggregating returns into a single measure that fully captures intertemporal substitution. Indeed, we show that there is no reason why return aggregation cannot be performed in the nonlinear setting of the Pricing Equation, since the latter is a linear function of individual returns. This forms the basis of a new test of rule-of-thumb behavior, which can be viewed as testing for the importance of rule-of-thumb consumers when the optimizing agent holds an equally-weighted portfolio or a weighted portfolio of traded assets. Using our setup, we find no signs of either rule-of-thumb behavior for U.S. consumers or of habit-formation in consumption decisions in econometric tests. Indeed, we show that the simple representative agent model with a CRRA utility is able to explain the time series data on consumption and aggregate returns. There, the intertemporal discount factor is significant and ranges from 0.956 to 0.969 while the relative risk-aversion coefficient is precisely estimated ranging from 0.829 to 1.126. There is no evidence of rejection in over-identifying-restriction tests.

Investment coordination failures and the confidence channel of fiscal policy

Este trabalho desenvolve um novo "canal de Confiança" da política fiscal e caracteriza a política ótima quando esse canal é levado em consideração. Para esse objetivo, utilizamos um modelo estático com (i) concorrência monopolística, (ii) custos de ajustamento fixos para investir, (iii) complementaridade estratégica devido a informação imperfeita com respeito a produtividade agregada, e (iv) bens privados como substitutos imperfeitos de bens privados. Este arcabouço acomoda a possibilidade de falhas de coordenação nos investimentos, mas apresenta um equilíbrio único. Mostramos que a política fiscal tem efeitos importantes na coordenação. Um aumento dos gastos do governo leva a uma maior demanda por bens privados. Mais importante, este também afeta as expectativas de ordem superior com relação a demanda das demais firmas, que amplifica os efeitos do aumento inicial da demanda devido a complementaridade estratégica nas decisões de investimento. Como as demais firmas estão se deparam com uma demanda maior, espera-se que estas invistam mais, que por sua vez, aumenta a demanda individual de cada firma, que aumenta os incentivos a investir. Denominamos isto como o "canal de confiança" da política fiscal. Sob a ameaça de falhas de coordenação, a política fiscal ótima prescreve produzir além do ponto em que o benefício marginal resultante do consumo de bens públicos é igual ao custo marginal desses bens. Este benefício adicional vem do fato de que a política fiscal pode ampliar a coordenação dos investimentos.

Credit borrowing constraints in a DSGE framework: income vs. housing

Credit market in Brazil distinguishes from advanced economies in many aspects. One of them is related to collaterals for households borrowing. This work proposes a DSGE framework, based on Gerali et al.(2010), to analyse one pecularity of Brazillian credit market: payroll-deducted personal loans. To original model, we added the possibility to households contract long term debt and compare to differents types of credit constrains: one based on housing and other based on future income. We callibrate and estimate the model to Brazil, using Bayesian technique. Results show that, in a economy where credit constraints are based on income, responses to shocks appear to be stronger, at first, but dissipate faster. This occurs because income responds quickly to shock than housing prices, so does amount available to loans. In order to smooth consumption, agents compensate lower income and borrowing by increasing working hours, restoring loans and debt in a shorter time.