Expectativas socialmente construídas: fundamentos, formalização e resultados exploratórios

Esta tese é uma discussão crítica, sob a ótica da formação de expectativas, da relação que se interpõe entre ciência econômica, como corpo de conhecimento, e seus agentes. Primeiro, examinamos abordagens relevantes sobre expectativas na análise econômica, indicando suas insuficiências. Argumentamos que a incorporação de expectativa, em qualquer tratamento analítico, deve envolver, principalmente, fundamentos epistêmicos. Segundo, sob a perspectiva da teoria de modernidade reflexiva desenvolvida por Anthony Giddens, buscamos identificar bases plausíveis para uma teoria de expectativa econômica. Concluímos que o processo de formação de expectativa é construção social, a partir da interdependência entre expertos e leigos. Denominamos esta conclusão por hipótese de expectativas socialmente construídas (HESC). Terceiro, propusemos um arcabouço analítico para incorporar a HESC. Basicamente, informação de expectativa se difunde através da mídia e do contato face a face entre agentes. Nova informação não resulta necessariamente em revisão de expectativas, o que vai depender, principalmente, de conhecimento econômico e vizinhança do agente. Por último, um exemplo de aplicação: o modelo-HESC foi submetido a três experimentos macroeconômicos, e seus resultados comparados àqueles obtidos por Mankiw e Reis (2002). A primeira conclusão desta tese é metodológica: expectativas dos agentes em modelos macroeconômicos não são determinadas a partir de equações do próprio modelo. A segunda é normativa: conhecimento e vizinhança são capazes de perpetuar ineficiências decorrentes de erros de expectativas. A terceira está relacionado com economia positiva: as diferenças entre os resultados do modelo de informação-rígida obtidos pelos autores acima e aqueles do modelo-HESC apontam para novas possibilidades explanatórias.

Testing the long-run implications of the expectation hypothesis using cointegration techniques with structural change

This paper investigates whether or not multivariate cointegrated process with structural change can describe the Brazilian term structure of interest rate data from 1995 to 2006. In this work the break point and the number of cointegrated vector are assumed to be known. The estimated model has four regimes. Only three of them are statistically different. The first starts at the beginning of the sample and goes until September of 1997. The second starts at October of 1997 until December of 1998. The third starts at January of 1999 and goes until the end of the sample. It is used monthly data. Models that allows for some similarities across the regimes are also estimated and tested. The models are estimated using the Generalized Reduced-Rank Regressions developed by Hansen (2003). All imposed restrictions can be tested using likelihood ratio test with standard asymptotic 1 qui-squared distribution. The results of the paper show evidence in favor of the long run implications of the expectation hypothesis for Brazil.

Stochastic growth and monetary policy: the impacts on the term structure of interest rates

This paper builds a simple, empirically-verifiable rational expectations model for term structure of nominal interest rates analysis. It solves an stochastic growth model with investment costs and sticky inflation, susceptible to the intervention of the monetary authority following a policy rule. The model predicts several patterns of the term structure which are in accordance to observed empirical facts: (i) pro-cyclical pattern of the level of nominal interest rates; (ii) countercyclical pattern of the term spread; (iii) pro-cyclical pattern of the curvature of the yield curve; (iv) lower predictability of the slope of the middle of the term structure; and (v) negative correlation of changes in real rates and expected inflation at short horizons.

Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons

The objective of this article is to study (understand and forecast) spot metal price levels and changes at monthly, quarterly, and annual horizons. The data to be used consists of metal-commodity prices in a monthly frequency from 1957 to 2012 from the International Financial Statistics of the IMF on individual metal series. We will also employ the (relatively large) list of co-variates used in Welch and Goyal (2008) and in Hong and Yogo (2009) , which are available for download. Regarding short- and long-run comovement, we will apply the techniques and the tests proposed in the common-feature literature to build parsimonious VARs, which possibly entail quasi-structural relationships between different commodity prices and/or between a given commodity price and its potential demand determinants. These parsimonious VARs will be later used as forecasting models to be combined to yield metal-commodity prices optimal forecasts. Regarding out-of-sample forecasts, we will use a variety of models (linear and non-linear, single equation and multivariate) and a variety of co-variates to forecast the returns and prices of metal commodities. With the forecasts of a large number of models (N large) and a large number of time periods (T large), we will apply the techniques put forth by the common-feature literature on forecast combinations. The main contribution of this paper is to understand the short-run dynamics of metal prices. We show theoretically that there must be a positive correlation between metal-price variation and industrial-production variation if metal supply is held fixed in the short run when demand is optimally chosen taking into account optimal production for the industrial sector. This is simply a consequence of the derived-demand model for cost-minimizing firms. Our empirical evidence fully supports this theoretical result, with overwhelming evidence that cycles in metal prices are synchronized with those in industrial production. This evidence is stronger regarding the global economy but holds as well for the U.S. economy to a lesser degree. Regarding forecasting, we show that models incorporating (short-run) commoncycle restrictions perform better than unrestricted models, with an important role for industrial production as a predictor for metal-price variation. Still, in most cases, forecast combination techniques outperform individual models.

Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons

The objective of this article is to study (understand and forecast) spot metal price levels and changes at monthly, quarterly, and annual frequencies. Data consists of metal-commodity prices at a monthly and quarterly frequencies from 1957 to 2012, extracted from the IFS, and annual data, provided from 1900-2010 by the U.S. Geological Survey (USGS). We also employ the (relatively large) list of co-variates used in Welch and Goyal (2008) and in Hong and Yogo (2009). We investigate short- and long-run comovement by applying the techniques and the tests proposed in the common-feature literature. One of the main contributions of this paper is to understand the short-run dynamics of metal prices. We show theoretically that there must be a positive correlation between metal-price variation and industrial-production variation if metal supply is held fixed in the short run when demand is optimally chosen taking into account optimal production for the industrial sector. This is simply a consequence of the derived-demand model for cost-minimizing firms. Our empirical evidence fully supports this theoretical result, with overwhelming evidence that cycles in metal prices are synchronized with those in industrial production. This evidence is stronger regarding the global economy but holds as well for the U.S. economy to a lesser degree. Regarding out-of-sample forecasts, our main contribution is to show the benefits of forecast-combination techniques, which outperform individual-model forecasts - including the random-walk model. We use a variety of models (linear and non-linear, single equation and multivariate) and a variety of co-variates and functional forms to forecast the returns and prices of metal commodities. Using a large number of models (N large) and a large number of time periods (T large), we apply the techniques put forth by the common-feature literature on forecast combinations. Empirically, we show that models incorporating (short-run) common-cycle restrictions perform better than unrestricted models, with an important role for industrial production as a predictor for metal-price variation.

The role of no-arbitrage on forecasting: lessons from a parametric term structure model

Parametric term structure models have been successfully applied to innumerous problems in fixed income markets, including pricing, hedging, managing risk, as well as studying monetary policy implications. On their turn, dynamic term structure models, equipped with stronger economic structure, have been mainly adopted to price derivatives and explain empirical stylized facts. In this paper, we combine flavors of those two classes of models to test if no-arbitrage affects forecasting. We construct cross section (allowing arbitrages) and arbitrage-free versions of a parametric polynomial model to analyze how well they predict out-of-sample interest rates. Based on U.S. Treasury yield data, we find that no-arbitrage restrictions significantly improve forecasts. Arbitrage-free versions achieve overall smaller biases and Root Mean Square Errors for most maturities and forecasting horizons. Furthermore, a decomposition of forecasts into forward-rates and holding return premia indicates that the superior performance of no-arbitrage versions is due to a better identification of bond risk premium.

Does Regulation matter? Institutional dimension of the 2008 financial crisis

Why did house prices fall in 2007‐2009? This is the fundamental question to most Americans, and to those who lent them money. Most homeowners did not care why residential real estate prices rose. They assumed prices always rose, and they should simply enjoy their good fortune. It was not until prices began to fall that people were left searching for answers. How much did regulation or lack thereof play in the role of the devastation? To what degree did greed and unrealistic consumer expectation have on the real estate bubble? Using existing literature as well as face to face interviews of experienced leaders within the real estate industry in California who experienced both the up and down of the real estate cycle, the overarching purpose of this study is to investigate the opinions and beliefs of the leaders and drivers within the real estate industry about the cause of the real estate bubble that occurred sharply in 2008 . Specifically, this project will focus on the opinions of real estate industry leaders who worked in the center of the subprime universe located in Irvine, California, during 2004‐2008. Comparing the mainstream beliefs with the interviewees it is fair to say that the main finding in the mainstream beliefs are reflected very well with the finding of the subject’s opinion. The thesis is divided into 6 chapters starting with “introduction”, followed by chapter 2 “Literature Review”. Chapter 3 is “Research Methodology” followed by chapter 4 “Data Presentation”. Finally, the results are discussed in chapter 5 “Analysis and Discussion” and conclusions in Chapter 6.

Dynamics of micro-entrepeneurial activities

This paper generates and organizes stylized facts related to the dynamics of selfemployment activities in Brazil. The final purpose is to help the design of policies to assist micro-entrepreneurial units. The 'first part of the paper uses as a main tool of analysis transitional data constructed from household surveys. The longitudinal information used covers three transition horizons: 1-month, 12-month and 5-year periods. Quantitative flows analysis assesses the main origins, destinies and various types of risks assumed by microentrepreneurial activities. Complementarily, logistic regressions provides evidence on the main characteristics and resources of micro-entrepreneurial units. In particular, we use the movements from self-employment to employer activities as measures of entrepreneurial success. We also use these transitions as measures of employment creation intensity within the self-employed segment.The second part of the paper explores various data sources. First, we attempt to analyze the life-cycle trajectories and determinants of self-employment. We use cohort data constructed from PME and qualitative data on financial and work history factors related to the opening of small bussiness from the informal firms survey implemented during 1994. Second, we apply a standart Mincerian wage equation approach to self-employment profits. This exerci se attempts to capture the correlation patterns between micro-entrepreneurial performance and a variety of firms leveI variables present in the 1994 Informal Survey. Finally, we use a a survey on the poor enterpreneurs of Rocinha favela as a laboratory to study poor entrepreneurs resources and behavior.In sum, the main questions pursued in the paper are: i) who are the Brazilian selfemployed?; ii) in particular: what is relative importance among the self-employed of subsistence activities versus those activities with growth and capital accumulation potential?; iii) what are the main static and dynamic determinants ofmicro-entrepreneurial success?; iv) what is the degree ofrisk associated with micro-entrepreneurial activities in Brazil?; v) What is the life-cycle profile of self-employment?; vi) what are the main constraints on poor entrepreneurs activities?.

Pricing and hedging of oil futures : a unifying approach

We develop and empirically test a continuous time equilibrium model for the pricing of oil futures. The model provides a link between no-arbitrage models and expectation oriented models. It highlights the role of inventories for the identification of different pricing regimes. In an empirical study the hedging performance of our model is compared with five other one- and two-factor pricing models. The hedging problem considered is related to Metallgesellschaft´s strategy to hedge long-term forward commitments with short-term futures. The results show that the downside risk distribution of our inventory based model stochastically dominates those of the other models.

In search of exchange rate predictability : a study about accuracy, consistency, and granger causality of forecasts generated by a Taylor Rule Model

Este estudo investiga o poder preditivo fora da amostra, um mês à frente, de um modelo baseado na regra de Taylor para previsão de taxas de câmbio. Revisamos trabalhos relevantes que concluem que modelos macroeconômicos podem explicar a taxa de câmbio de curto prazo. Também apresentamos estudos que são céticos em relação à capacidade de variáveis macroeconômicas preverem as variações cambiais. Para contribuir com o tema, este trabalho apresenta sua própria evidência através da implementação do modelo que demonstrou o melhor resultado preditivo descrito por Molodtsova e Papell (2009), o “symmetric Taylor rule model with heterogeneous coefficients, smoothing, and a constant”. Para isso, utilizamos uma amostra de 14 moedas em relação ao dólar norte-americano que permitiu a geração de previsões mensais fora da amostra de janeiro de 2000 até março de 2014. Assim como o critério adotado por Galimberti e Moura (2012), focamos em países que adotaram o regime de câmbio flutuante e metas de inflação, porém escolhemos moedas de países desenvolvidos e em desenvolvimento. Os resultados da nossa pesquisa corroboram o estudo de Rogoff e Stavrakeva (2008), ao constatar que a conclusão da previsibilidade da taxa de câmbio depende do teste estatístico adotado, sendo necessária a adoção de testes robustos e rigorosos para adequada avaliação do modelo. Após constatar não ser possível afirmar que o modelo implementado provém previsões mais precisas do que as de um passeio aleatório, avaliamos se, pelo menos, o modelo é capaz de gerar previsões “racionais”, ou “consistentes”. Para isso, usamos o arcabouço teórico e instrumental definido e implementado por Cheung e Chinn (1998) e concluímos que as previsões oriundas do modelo de regra de Taylor são “inconsistentes”. Finalmente, realizamos testes de causalidade de Granger com o intuito de verificar se os valores defasados dos retornos previstos pelo modelo estrutural explicam os valores contemporâneos observados. Apuramos que o modelo fundamental é incapaz de antecipar os retornos realizados.