Estimation of DSGE Models: A Monte Carlo Analysis

Neste trabalho investigamos as propriedades em pequena amostra e a robustez das estimativas dos parâmetros de modelos DSGE. Tomamos o modelo de Smets and Wouters (2007) como base e avaliamos a performance de dois procedimentos de estimação: Método dos Momentos Simulados (MMS) e Máxima Verossimilhança (MV). Examinamos a distribuição empírica das estimativas dos parâmetros e sua implicação para as análises de impulso-resposta e decomposição de variância nos casos de especificação correta e má especificação. Nossos resultados apontam para um desempenho ruim de MMS e alguns padrões de viés nas análises de impulso-resposta e decomposição de variância com estimativas de MV nos casos de má especificação considerados.

Semiparametric estimation and inference using doubly robust moment conditions

We study semiparametric two-step estimators which have the same structure as parametric doubly robust estimators in their second step. The key difference is that we do not impose any parametric restriction on the nuisance functions that are estimated in a first stage, but retain a fully nonparametric model instead. We call these estimators semiparametric doubly robust estimators (SDREs), and show that they possess superior theoretical and practical properties compared to generic semiparametric two-step estimators. In particular, our estimators have substantially smaller first-order bias, allow for a wider range of nonparametric first-stage estimates, rate-optimal choices of smoothing parameters and data-driven estimates thereof, and their stochastic behavior can be well-approximated by classical first-order asymptotics. SDREs exist for a wide range of parameters of interest, particularly in semiparametric missing data and causal inference models. We illustrate our method with a simulation exercise.

Três ensaios sobre política monetária e crédito

In the first essay, "Determinants of Credit Expansion in Brazil", analyzes the determinants of credit using an extensive bank level panel dataset. Brazilian economy has experienced a major boost in leverage in the first decade of 2000 as a result of a set factors ranging from macroeconomic stability to the abundant liquidity in international financial markets before 2008 and a set of deliberate decisions taken by President Lula's to expand credit, boost consumption and gain political support from the lower social strata. As relevant conclusions to our investigation we verify that: credit expansion relied on the reduction of the monetary policy rate, international financial markets are an important source of funds, payroll-guaranteed credit and investment grade status affected positively credit supply. We were not able to confirm the importance of financial inclusion efforts. The importance of financial sector sanity indicators of credit conditions cannot be underestimated. These results raise questions over the sustainability of this expansion process and financial stability in the future. The second essay, “Public Credit, Monetary Policy and Financial Stability”, discusses the role of public credit. The supply of public credit in Brazil has successfully served to relaunch the economy after the Lehman-Brothers demise. It was later transformed into a driver for economic growth as well as a regulation device to force private banks to reduce interest rates. We argue that the use of public funds to finance economic growth has three important drawbacks: it generates inflation, induces higher loan rates and may induce financial instability. An additional effect is the prevention of market credit solutions. This study contributes to the understanding of the costs and benefits of credit as a fiscal policy tool. The third essay, “Bayesian Forecasting of Interest Rates: Do Priors Matter?”, discusses the choice of priors when forecasting short-term interest rates. Central Banks that commit to an Inflation Target monetary regime are bound to respond to inflation expectation spikes and product hiatus widening in a clear and transparent way by abiding to a Taylor rule. There are various reports of central banks being more responsive to inflationary than to deflationary shocks rendering the monetary policy response to be indeed non-linear. Besides that there is no guarantee that coefficients remain stable during time. Central Banks may switch to a dual target regime to consider deviations from inflation and the output gap. The estimation of a Taylor rule may therefore have to consider a non-linear model with time varying parameters. This paper uses Bayesian forecasting methods to predict short-term interest rates. We take two different approaches: from a theoretic perspective we focus on an augmented version of the Taylor rule and include the Real Exchange Rate, the Credit-to-GDP and the Net Public Debt-to-GDP ratios. We also take an ”atheoretic” approach based on the Expectations Theory of the Term Structure to model short-term interest. The selection of priors is particularly relevant for predictive accuracy yet, ideally, forecasting models should require as little a priori expert insight as possible. We present recent developments in prior selection, in particular we propose the use of hierarchical hyper-g priors for better forecasting in a framework that can be easily extended to other key macroeconomic indicators.

Forecasting Multivariate Time Series under Present-Value-Model Short- and Long-run Co-movement Restrictions

This paper has two original contributions. First, we show that the present value model (PVM hereafter), which has a wide application in macroeconomics and fi nance, entails common cyclical feature restrictions in the dynamics of the vector error-correction representation (Vahid and Engle, 1993); something that has been already investigated in that VECM context by Johansen and Swensen (1999, 2011) but has not been discussed before with this new emphasis. We also provide the present value reduced rank constraints to be tested within the log-linear model. Our second contribution relates to forecasting time series that are subject to those long and short-run reduced rank restrictions. The reason why appropriate common cyclical feature restrictions might improve forecasting is because it finds natural exclusion restrictions preventing the estimation of useless parameters, which would otherwise contribute to the increase of forecast variance with no expected reduction in bias. We applied the techniques discussed in this paper to data known to be subject to present value restrictions, i.e. the online series maintained and up-dated by Shiller. We focus on three different data sets. The fi rst includes the levels of interest rates with long and short maturities, the second includes the level of real price and dividend for the S&P composite index, and the third includes the logarithmic transformation of prices and dividends. Our exhaustive investigation of several different multivariate models reveals that better forecasts can be achieved when restrictions are applied to them. Moreover, imposing short-run restrictions produce forecast winners 70% of the time for target variables of PVMs and 63.33% of the time when all variables in the system are considered.

O fator comum associado à dinâmica de preços das commodities : a relação de cointegração e o fator dinâmico

Este trabalho analisa a importância dos fatores comuns na evolução recente dos preços dos metais no período entre 1995 e 2013. Para isso, estimam-se modelos cointegrados de VAR e também um modelo de fator dinâmico bayesiano. Dado o efeito da financeirização das commodities, DFM pode capturar efeitos dinâmicos comuns a todas as commodities. Além disso, os dados em painel são aplicados para usar toda a heterogeneidade entre as commodities durante o período de análise. Nossos resultados mostram que a taxa de juros, taxa efetiva do dólar americano e também os dados de consumo têm efeito permanente nos preços das commodities. Observa-se ainda a existência de um fator dinâmico comum significativo para a maioria dos preços das commodities metálicas, que tornou-se recentemente mais importante na evolução dos preços das commodities.

A model of rural conflict : violence and land reform policy in Brazil

In the past ten years the struggle for land in Brazil has taken the shape of invasions of private land by welI organized groups of land less squatters. It is argued in this paper that these invasions and the resulting contlicts are a direct response to the land reform program which has been adopted by the govemment since 1985. which is based on the expropriation of farms and the creation of settlement projects. The set of formal and informal institutions which compromise the land reform program are used as the background for a game-theory model of rural contlicts. T estable implications are derived trom this model with particular emphasis on the etfect of policy variables on violence. These are then tested with panel data at state levei from 1988 to 1995. - It is shown that govemment policy which has the intent of reducing the amount of violence has the opposite etfect of leading to more incentives for contlicts.

Implications of ernbodied technological change for development economics

Employing a embodied technologic change model in which the time decision of scrapping old vintages of capital and adopt newer one is endogenous we show that the elasticity of substitutions among capital and labor plays a key role in determining the optimum life span of capital. In particular, for the CD case the life span of capital does not depend on the relative price of it. The estimation of the model's long-run investment function shows, for a Panel data set consisting of 125 economies for 25 years, that the price elasticity of investment is lower than one; we rejected the CD specification. Our calibration for the US suggests 0.4 for the technical elasticity of substitution. In order to get a theoretical consistent concept of aggregate capital we derive the relative price profile for a shadow second-hand market for capital. The shape of the model's theoretical price curve reproduces the empírical estimation of it. \lVe plug the calibrate version of the long-run solution of the model to a cross-section of economies data set to get the implied TFP, that is, the part of the productivity which is not explained by the model. We show that the mo dei represent a good improvement, comparing to the standard neoc!assical growth model with CD production function and disembodied technical change, in accounting the world diversity in productivity. In addition the model describes the fact that a very poor economy can experience fast growth based on capital accumulation until the point of becoming a middle income economy; from this point on it has to rely on TFP increase in order to keep growing.

Using a panel structure to discuss the Feldstein-Horioka puzzle in developing countries

The purpose of this paper is to test the implications of current account solvency for the savinginvestment correlation in developing countries. Since solvency is a long-run phenomenon, and given that the power of the standard unit root and cointegration tests is low, we exploit the panel structure of the sample of 29 developing countries. We find evidence that saving and investment are cointegrated and that the current account is stationary. Therefore, the Feldstein-Horioka correlations are not a puzzle in the sense they reflect the intertemporal budget constraint. The same results are obtained for different subsamples (Africa, Asia, and Latin America) and for different periods of time (1960-74 and 1975-96). We, then, suggest that an error correction model should distinguish between the long-run correlation, which reflects the solvency condition, and the short-run correlation, which could measure capital mobility.

Bayesian analysis of extreme events with threshold estimation

The aim of this paper is to analyze extremal events using Generalized Pareto Distributions (GPD), considering explicitly the uncertainty about the threshold. Current practice empirically determines this quantity and proceeds by estimating the GPD parameters based on data beyond it, discarding all the information available be10w the threshold. We introduce a mixture model that combines a parametric form for the center and a GPD for the tail of the distributions and uses all observations for inference about the unknown parameters from both distributions, the threshold inc1uded. Prior distribution for the parameters are indirectly obtained through experts quantiles elicitation. Posterior inference is available through Markov Chain Monte Carlo (MCMC) methods. Simulations are carried out in order to analyze the performance of our proposed mode1 under a wide range of scenarios. Those scenarios approximate realistic situations found in the literature. We also apply the proposed model to a real dataset, Nasdaq 100, an index of the financiai market that presents many extreme events. Important issues such as predictive analysis and model selection are considered along with possible modeling extensions.

Deunionization in the US: a panel data analysis from 1973 to 1999

There are four different hypotheses analyzed in the literature that explain deunionization, namely: the decrease in the demand for union representation by the workers; the impaet of globalization over unionization rates; teehnieal ehange and ehanges in the legal and politieal systems against unions. This paper aims to test alI ofthem. We estimate a logistie regression using panel data proeedure with 35 industries from 1973 to 1999 and eonclude that the four hypotheses ean not be rejeeted by the data. We also use a varianee analysis deeomposition to study the impaet of these variables over the drop in unionization rates. In the model with no demographic variables the results show that these economic (tested) variables can account from 10% to 12% of the drop in unionization. However, when we include demographic variables these tested variables can account from 10% to 35% in the total variation of unionization rates. In this case the four hypotheses tested can explain up to 50% ofthe total drop in unionization rates explained by the model.

Impactos da política fiscal e tributária no crescimento econômico

Utilizando uma adaptação do modelo de Telles e Mussolini (2014), o presente trabalho busca discutir as caracterizações da matriz tributária, discutindo como as variações na matriz tributária podem impactar na política fiscal. Discute-se com base na diferenciação dos impostos em cinco grupos, a saber: impostos sobre salários, impostos sobre investimentos, impostos sobre consumo, impostos sobre renda e riqueza, e impostos sobre comércio internacional, a partir dos quais argumenta-se quais seus impactos para a política fiscal, para a interação das variáveis econômicas e a evolução destas variáveis, assim como a relação entre a preferência por uma determinada estrutura tributária e o endividamento de um país. Após a discussão teórica, faz-se uma análise descritiva da evolução destas variáveis tributárias para cada categoria de tributo, relacionando a sua evolução no tempo para um grupo de 64 países, tomados a partir do trabalho de Telles e Mussolini (2014), assim como relacionando a sua evolução intertemporal. Por fim, faz-se uma análise da estrutura tributária destes países, discutindo, na análise dos dados em painel, os resultados para as estimativas em modelos de efeitos fixos e efeitos aleatórios, os resultados da estimação pelo modelo Arellano-Bond, e utilizando-se a abordagem instrumental pelo Método Generalizado dos Momentos, onde se conclui que a taxação sobre a riqueza e a taxação sobre o comércio internacional com fins de financiar o excesso de gastos do governo impacta de forma negativa na trajetória de crescimento, entre outros resultados.

Consumption-wealth ratio and expected stock returns: evidence from panel data

This paper investigates the role of consumption-wealth ratio on predicting future stock returns through a panel approach. We follow the theoretical framework proposed by Lettau and Ludvigson (2001), in which a model derived from a nonlinear consumer’s budget constraint is used to settle the link between consumption-wealth ratio and stock returns. Using G7’s quarterly aggregate and financial data ranging from the first quarter of 1981 to the first quarter of 2014, we set an unbalanced panel that we use for both estimating the parameters of the cointegrating residual from the shared trend among consumption, asset wealth and labor income, cay, and performing in and out-of-sample forecasting regressions. Due to the panel structure, we propose different methodologies of estimating cay and making forecasts from the one applied by Lettau and Ludvigson (2001). The results indicate that cay is in fact a strong and robust predictor of future stock return at intermediate and long horizons, but presents a poor performance on predicting one or two-quarter-ahead stock returns.

Asymptotic efficiency in an instrumental variable model

Esta dissertação se propõe ao estudo de inferência usando estimação por método generalizado dos momentos (GMM) baseado no uso de instrumentos. A motivação para o estudo está no fato de que sob identificação fraca dos parâmetros, a inferência tradicional pode levar a resultados enganosos. Dessa forma, é feita uma revisão dos mais usuais testes para superar tal problema e uma apresentação dos arcabouços propostos por Moreira (2002) e Moreira & Moreira (2013), e Kleibergen (2005). Com isso, o trabalho concilia as estatísticas utilizadas por eles para realizar inferência e reescreve o teste score proposto em Kleibergen (2005) utilizando as estatísticas de Moreira & Moreira (2013), e é obtido usando a teoria assintótica em Newey & McFadden (1984) a estatística do teste score ótimo. Além disso, mostra-se a equivalência entre a abordagem por GMM e a que usa sistema de equações e verossimilhança para abordar o problema de identificação fraca.

Invariant tests in an instrumental variables model with unknown data generating process

In this work we focus on tests for the parameter of an endogenous variable in a weakly identi ed instrumental variable regressionmodel. We propose a new unbiasedness restriction for weighted average power (WAP) tests introduced by Moreira and Moreira (2013). This new boundary condition is motivated by the score e ciency under strong identi cation. It allows reducing computational costs of WAP tests by replacing the strongly unbiased condition. This latter restriction imposes, under the null hypothesis, the test to be uncorrelated to a given statistic with dimension given by the number of instruments. The new proposed boundary condition only imposes the test to be uncorrelated to a linear combination of the statistic. WAP tests under both restrictions to perform similarly numerically. We apply the di erent tests discussed to an empirical example. Using data from Yogo (2004), we assess the e ect of weak instruments on the estimation of the elasticity of inter-temporal substitution of a CCAPM model.

Respiratory heat loss in the sheep: a comprehensive model

A model is presented for the respiratory heat loss in sheep, considering both the sensible heat lost by convection (C-R) and the latent heat eliminated by evaporation (E-R). A practical method is described for the estimation of the tidal volume as a function of the respiratory rate. Equations for C-R and E-R are developed and the relative importance of both heat transfer mechanisms is discussed. At air temperatures up to 30 degreesC sheep have the least respiratory heat loss at air vapour pressures above 1.6 kPa. At an ambient temperature of 40 degreesC respiratory loss of sensible heat can be nil; for higher temperatures the transfer by convection is negative and thus heat is gained. Convection is a mechanism of minor importance for the respiratory heat transfer in sheep at environmental temperatures above 30 degreesC. These observations show the importance of respiratory latent heat loss for thermoregulation of sheep in hot climates.