Previsão da inflação no Boletim Focus: uma avaliação

Este trabalho investiga e analisa as diferenças das taxas anuais de inflação realizadas com relação às previsões dos agentes econômicos do mercado para um ano à frente. Os índices analisados foram o IPCA, IPA-M, IGP-M e o IGP-DI. Referente à previsão dos agentes para cada índice, foi feito uma análise estatística e uma análise de séries temporais através do modelo ARIMA. Este último explicou o erro de previsão dos agentes econômicos através de valores passados, ou defasados, do próprio erro de previsão, além dos termos estocásticos.

Inflation persistence and flexible prices

The inability of rational expectation models with money supply rules to deliver inflation persistence following a transitory deviation of money growth from trend is due to the rapid adjustment of the price level to expected events. The observation of persistent inflation in macroeconomic data leads many economists to believe that prices adjust sluggishly and/or expectations must not be rational. Inflation persistence in U.S. data can be characterized by a vector autocorrelation function relating inflation and deviations of output from trend. In the vector autocorrelation function both inflation and output are highly persistent and there are significant positive dynamic cross-correlations relating inflation and output. This paper shows that a flexible-price general equilibrium business cycle model with money and a central bank using a Taylor rule can account for these patterns. There are no sticky prices and no liquidity effects. Agents decisions in a period are taken only after all shocks are observed. The monetary policy rule transforms output persistence into inflation persistence and creates positive cross-correlations between inflation and output.

A restatement of the welafare costs of inflation. The wast of scarce resources in the manufacturing , banking and household sectors

Lucas (2000) estimates that the US welfare costs of inflation are around 1% of GDP. This measurement is consistent with a speci…c distorting channel in terms of the Bailey triangle under the demand for monetary base schedule (outside money): the displacement of resources from the production of consumption goods to the household transaction time à la Baumol. Here, we consider also several new types of distortions in the manufacturing and banking industries. Our new evidences show that both banks and firms demand special occupational employments to avoid the inflation tax. We de…ne the concept of ”the foat labor”: The occupational employments that are aflected by the in‡ation rates. More administrative workers are hired relatively to the bluecollar workers for producing consumption goods. This new phenomenon makes the manufacturing industry more roundabout. To take into account this new stylized fact and others, we redo at same time both ”The model 5: A Banking Sector -2” formulated by Lucas (1993) and ”The Competitive Banking System” proposed by Yoshino (1993). This modelling allows us to characterize better the new types of misallocations. We …nd that the maximum value of the resources wasted by the US economy happened in the years 1980-81, after the 2nd oil shock. In these years, we estimate the excess resources that are allocated for every speci…c distorting channel: i) The US commercial banks spent additional resources of around 2% of GDP; ii) For the purpose of the firm foating time were used between 2.4% and 4.1% of GDP); and iii) For the household transaction time were allocated between 3.1% and 4.5 % of GDP. The Bailey triangle under the demand for the monetary base schedule represented around 1% of GDP, which is consistent with Lucas (2000). We estimate that the US total welfare costs of in‡ation were around 10% of GDP in terms of the consumption goods foregone. The big di¤erence between our results and Lucas (2000) are mainly due to the Harberger triangle in the market for loans (inside money) which makes part of the household transaction time, of the …rm ‡oat labor and of the distortion in the banking industry. This triangle arises due to the widening interest rates spread in the presence of a distorting inflation tax and under a fractionally reserve system. The Harberger triangle can represent 80% of the total welfare costs of inflation while the remaining percentage is split almost equally between the Bailey triangle and the resources used for the bank services. Finally, we formulate several theorems in terms of the optimal nonneutral monetary policy so as to compare with the classical monetary theory.

Inflation targeting, credibility and coordination aspects

There are plenty of economic studies pointing out some requirements, like the inexistence of fiscal dominance, for inflation targeting framework be implemented in successful (credible) way. Essays on how public targets could be used in the absence of such requirements are unusual. In this papel' we appraise how central banks could use inflation targeting before soundness economic fundamentaIs have been achieved. First, based on concise framework, where confidence crises and imperfect information are neglected, we conclude that less ambitious (greater) target for inflation increases the credibility in the precommitment. Optimal target is higher than the one obtained using the Cukierman-Liviatan [7] model, where increasing credibility effect is not considered. Second, extending the model to make confidence crises possible, multiple equilibria solutions becomes possible too. In this case, to set greater targets for inflation may stimulate confidence crises and reduce the policymaker credibility. On the other hand, multiple (bad) equilibria may be avoided. The optimal target depends on the likelihood of each equilibrium be selected. Finally, when perturbing common knowledge uniqueness is restored even considering confidence crises, as in Morris-Shin[ 14]. The first result, i.e. less ambitious target for inflation increases credibility in precommitment, is also recovered. Adding a precise public signal, cOOl'dinated self-fulfilling actions and equilibrium multiplicity may still exist for some lack of common knowledge (as in Angeleto and Weming[l]). In this case, to set greater targets for inflation may stimulate confidence crisis again, reducing the policymaker credibility. From another aspect, multiple (bad) equilibria may be avoided. Optimal policy prescriptions depend on the likelihood of each equilibrium be selected. Results also indicate that more precise public information may open the door for bad equilibrium, contrary to the conventional wisdom that more central oank transparency is always good when considering inflation targeting framework.

Time-dependent or state-dependent pricing? Evidence from firms’ response to inflation shocks

This paper proposes a test for distinguishing between time-dependent and state-dependent pricing based on whether the timing of pricing changes is affected by realized or expeted inflation. Using Brazilian data and exploring a large discrepancy between realized and expected inflation in 2002-3, we obtain a strong relation between expected inflation and duration of price spells, but little effect of inflation shocks on the frequency of price adjustment. The results thus support models with timedependent pricing, where the timing for following changes is optimally chosen whenever firms adjust prices

Apresentação 10: “Inflation Targeting”, “Currency Regimes with Defaultable Debts” e Sistema Tributário na Presença de Informalidade e Evasão Fiscal…A disseminação internacional das pesquisas aplicadas relacionadas a agenda brasileira

Coordenadora: Goret P. Paulo

A Numerical method for the semilinear stochastic transport equation

Trabalho apresentado no XXXV CNMAC, Natal-RN, 2014.

Computer simulation of the stochastic transport equation

Trabalho apresentado no 37th Conference on Stochastic Processes and their Applications - July 28 - August 01, 2014 -Universidad de Buenos Aires

Numerical integration of coupled stochastic oscillators driven by Random Forces

Trabalho apresentado no International Conference on Scientific Computation And Differential Equations 2015

Convergence analysis of sampling-based decomposition methods for risk-averse multistage stochastic convex programs

We consider a class of sampling-based decomposition methods to solve risk-averse multistage stochastic convex programs. We prove a formula for the computation of the cuts necessary to build the outer linearizations of the recourse functions. This formula can be used to obtain an efficient implementation of Stochastic Dual Dynamic Programming applied to convex nonlinear problems. We prove the almost sure convergence of these decomposition methods when the relatively complete recourse assumption holds. We also prove the almost sure convergence of these algorithms when applied to risk-averse multistage stochastic linear programs that do not satisfy the relatively complete recourse assumption. The analysis is first done assuming the underlying stochastic process is interstage independent and discrete, with a finite set of possible realizations at each stage. We then indicate two ways of extending the methods and convergence analysis to the case when the process is interstage dependent.

Multistep stochastic mirror descent for risk-averse convex stochastic programs based on extended polyhedral risk measures

We consider risk-averse convex stochastic programs expressed in terms of extended polyhedral risk measures. We derive computable con dence intervals on the optimal value of such stochastic programs using the Robust Stochastic Approximation and the Stochastic Mirror Descent (SMD) algorithms. When the objective functions are uniformly convex, we also propose a multistep extension of the Stochastic Mirror Descent algorithm and obtain con dence intervals on both the optimal values and optimal solutions. Numerical simulations show that our con dence intervals are much less conservative and are quicker to compute than previously obtained con dence intervals for SMD and that the multistep Stochastic Mirror Descent algorithm can obtain a good approximate solution much quicker than its nonmultistep counterpart. Our con dence intervals are also more reliable than asymptotic con dence intervals when the sample size is not much larger than the problem size.

Non-asymptotic confidence bounds for the optimal value of a stochastic program

We discuss a general approach to building non-asymptotic confidence bounds for stochastic optimization problems. Our principal contribution is the observation that a Sample Average Approximation of a problem supplies upper and lower bounds for the optimal value of the problem which are essentially better than the quality of the corresponding optimal solutions. At the same time, such bounds are more reliable than “standard” confidence bounds obtained through the asymptotic approach. We also discuss bounding the optimal value of MinMax Stochastic Optimization and stochastically constrained problems. We conclude with a small simulation study illustrating the numerical behavior of the proposed bounds.

Stochastic discount factor bounds and rare events: a review

We aim to provide a review of the stochastic discount factor bounds usually applied to diagnose asset pricing models. In particular, we mainly discuss the bounds used to analyze the disaster model of Barro (2006). Our attention is focused in this disaster model since the stochastic discount factor bounds that are applied to study the performance of disaster models usually consider the approach of Barro (2006). We first present the entropy bounds that provide a diagnosis of the analyzed disaster model which are the methods of Almeida and Garcia (2012, 2016); Ghosh et al. (2016). Then, we discuss how their results according to the disaster model are related to each other and also present the findings of other methodologies that are similar to these bounds but provide different evidence about the performance of the framework developed by Barro (2006).