The importance of common cyclical features in VAR analysis: a Monte-Carlo study

Despite the commonly held belief that aggregate data display short-run comovement, there has been little discussion about the econometric consequences of this feature of the data. We use exhaustive Monte-Carlo simulations to investigate the importance of restrictions implied by common-cyclical features for estimates and forecasts based on vector autoregressive models. First, we show that the ìbestî empirical model developed without common cycle restrictions need not nest the ìbestî model developed with those restrictions. This is due to possible differences in the lag-lengths chosen by model selection criteria for the two alternative models. Second, we show that the costs of ignoring common cyclical features in vector autoregressive modelling can be high, both in terms of forecast accuracy and efficient estimation of variance decomposition coefficients. Third, we find that the Hannan-Quinn criterion performs best among model selection criteria in simultaneously selecting the lag-length and rank of vector autoregressions.

Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions

We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We consider model selection criteria which have data-dependent penalties for a lack of parsimony, as well as the traditional ones. We suggest a new procedure which is a hybrid of traditional criteria and criteria with data-dependant penalties. In order to compute the fit of each model, we propose an iterative procedure to compute the maximum likelihood estimates of parameters of a VAR model with short-run and long-run restrictions. Our Monte Carlo simulations measure the improvements in forecasting accuracy that can arise from the joint determination of lag-length and rank, relative to the commonly used procedure of selecting the lag-length only and then testing for cointegration.

Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions

We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We consider model selection criteria which have data-dependent penalties as well as the traditional ones. We suggest a new two-step model selection procedure which is a hybrid of traditional criteria and criteria with data-dependant penalties and we prove its consistency. Our Monte Carlo simulations measure the improvements in forecasting accuracy that can arise from the joint determination of lag-length and rank using our proposed procedure, relative to an unrestricted VAR or a cointegrated VAR estimated by the commonly used procedure of selecting the lag-length only and then testing for cointegration. Two empirical applications forecasting Brazilian inflation and U.S. macroeconomic aggregates growth rates respectively show the usefulness of the model-selection strategy proposed here. The gains in different measures of forecasting accuracy are substantial, especially for short horizons.

Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions

We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We consider model selection criteria which have data-dependent penalties as well as the traditional ones. We suggest a new two-step model selection procedure which is a hybrid of traditional criteria and criteria with data-dependant penalties and we prove its consistency. Our Monte Carlo simulations measure the improvements in forecasting accuracy that can arise from the joint determination of lag-length and rank using our proposed procedure, relative to an unrestricted VAR or a cointegrated VAR estimated by the commonly used procedure of selecting the lag-length only and then testing for cointegration. Two empirical applications forecasting Brazilian in ation and U.S. macroeconomic aggregates growth rates respectively show the usefulness of the model-selection strategy proposed here. The gains in di¤erent measures of forecasting accuracy are substantial, especially for short horizons.

Divisia indexes, money and welfare

We suggest the use of a particular Divisia index for measuring welfare losses due to interest rate wedges and in‡ation. Compared to the existing options in the literature: i) when the demands for the monetary assets are known, closed-form solutions for the welfare measures can be obtained at a relatively lower algebraic cost; ii) less demanding integrability conditions allow for the recovery of welfare measures from a larger class of demand systems and; iii) when the demand speci…cations are not known, using an index number entitles the researcher to rank di¤erent vectors of opportunity costs directly from market observations. We use two examples to illustrate the method.

Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions

We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We suggest a new two-step model selection procedure which is a hybrid of traditional criteria and criteria with data-dependant penalties and we prove its consistency. A Monte Carlo study explores the finite sample performance of this procedure and evaluates the forecasting accuracy of models selected by this procedure. Two empirical applications confirm the usefulness of the model selection procedure proposed here for forecasting.

Criação e teste de uma escala para avaliação da estratégia de gestão do conhecimento : aplicação a um escritório de propriedade intelectual

Esta dissertação objetiva avaliar como as empresas organizam sua estratégia para gestão do conhecimento. Basicamente dois modelos estratégicos são apresentados na literatura: a codificação e a personalização. No entanto, há uma questão que se apresenta na literatura que se refere à importância do foco prioritário em apenas um dos modelos estratégicos citados. Como objetivo principal, pretende-se apresentar uma escala que possa analisar se uma empresa líder em seu segmento realmente possui um foco estratégico com relação à gestão do conhecimento. Durante o desenvolvimento deste trabalho, será percorrido um referencial teórico que busca explicar como a gestão do conhecimento se tomou importante para a estratégia das empresas, tocando em pontos como características da Era da Informação e conceitos básicos da gestão do conhecimento, englobando modelos teóricos que buscam explicar como o conhecimento é criado e transferido dentro das empresas. Um modelo para mensuração do foco estratégico de uma empresa será proposto. Este modelo será composto de indicadores estruturados em forma de um questionário. Para cada indicador haverá uma escala de avaliação e o conjunto do questionário buscará traduzir o foco estratégico citado. Por fim, o questionário será testado em uma empresa de Propriedade Intelectual e serão feitas análises estatísticas para avaliação do mesmo. Para isto será utilizado o procedimento da análise fatorial do tipo confirmatória. Trata-se de uma ferramenta estatística que possibilita uma avaliação tanto do modelo de análise, quanto do modelo estrutural.

Estudo sobre as preferências dos usuários dos demonstrativos financeiros em relação ao uso de terminologia descritiva, versus terminologia técnica nos relatórios contábeis das empresas

O propósito deste estudo foi determinar se os grupos de usuários com níveis diferenciados de sofisticação em conhecimentos contábeis, diferiam em relação às preferências por terminologias contábeis técnicas versus terminologias contábeis técnicas descritivas. Examinou-se seis sinônimos para cada um dos dez conceitos escolhidos. Solicitou-se aos respondentes que classificassem os termos por ordem de preferência.

A Common-feature approach for testing present-value restrictions with financial data

It is well known that cointegration between the level of two variables (labeled Yt and yt in this paper) is a necessary condition to assess the empirical validity of a present-value model (PV and PVM, respectively, hereafter) linking them. The work on cointegration has been so prevalent that it is often overlooked that another necessary condition for the PVM to hold is that the forecast error entailed by the model is orthogonal to the past. The basis of this result is the use of rational expectations in forecasting future values of variables in the PVM. If this condition fails, the present-value equation will not be valid, since it will contain an additional term capturing the (non-zero) conditional expected value of future error terms. Our article has a few novel contributions, but two stand out. First, in testing for PVMs, we advise to split the restrictions implied by PV relationships into orthogonality conditions (or reduced rank restrictions) before additional tests on the value of parameters. We show that PV relationships entail a weak-form common feature relationship as in Hecq, Palm, and Urbain (2006) and in Athanasopoulos, Guillén, Issler and Vahid (2011) and also a polynomial serial-correlation common feature relationship as in Cubadda and Hecq (2001), which represent restrictions on dynamic models which allow several tests for the existence of PV relationships to be used. Because these relationships occur mostly with nancial data, we propose tests based on generalized method of moment (GMM) estimates, where it is straightforward to propose robust tests in the presence of heteroskedasticity. We also propose a robust Wald test developed to investigate the presence of reduced rank models. Their performance is evaluated in a Monte-Carlo exercise. Second, in the context of asset pricing, we propose applying a permanent-transitory (PT) decomposition based on Beveridge and Nelson (1981), which focus on extracting the long-run component of asset prices, a key concept in modern nancial theory as discussed in Alvarez and Jermann (2005), Hansen and Scheinkman (2009), and Nieuwerburgh, Lustig, Verdelhan (2010). Here again we can exploit the results developed in the common cycle literature to easily extract permament and transitory components under both long and also short-run restrictions. The techniques discussed herein are applied to long span annual data on long- and short-term interest rates and on price and dividend for the U.S. economy. In both applications we do not reject the existence of a common cyclical feature vector linking these two series. Extracting the long-run component shows the usefulness of our approach and highlights the presence of asset-pricing bubbles.

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.

Testing for super-exogeneity in the presence of common deterministic shifts

This paper introduces the concept of common deterministic shifts (CDS). This concept is simple, intuitive and relates to the common structure of shifts or policy interventions. We propose a Reduced Rank technique to investigate the presence of CDS. The proposed testing procedure has standard asymptotics and good small-sample properties. We further link the concept of CDS to that of superexogeneity. It is shown that CDS tests can be constructed which allow to test for super-exogeneity. The Monte Carlo evidence indicates that the CDS test for super-exogeneity dominates testing procedures proposed in the literature.

Growth process in business and social entrepreneurship: the case of Brazil

The purpose of the dissertation is to investigate in depth the difference between the challenges social and business entrepreneurs face in the growth phase of their business in the particular environment of Brazil. This objective has been achieved through a two-steps methodology. The first step is a set of in-depth interviews carried out with industry experts such as professors, venture capitalists, consultants, fund managers or people involved in the support of growing startups (i.e. accelerators). These interviews allowed, first, to build a general perspective on the environment entrepreneurs operate into and to identify a list of challenges entrepreneurs face in the growth process of their business. This list was completed with the additional challenges identified in the previous literature. The second step of the methodology was to test the relevance of these challenges in the mind and experience of social and traditional entrepreneurs. A questionnaire was then submitted to 145 social and 286 traditional entrepreneurs. The results were statistically analyzed to test the relative relevance of these challenges for one group of entrepreneurs with respect to the other. The outcome of the analysis was significant. The most relevant challenges identified were, for both groups, taxation, bureaucracy, finding the right employees, creating effective teams, measuring firm performance and social value creation and obtaining funds. On the other side motivation, innovation, competition and lack of market space for growth represented the least relevant issues in the minds of entrepreneurs. This rank however did not differ significantly from social to traditional entrepreneurs. This testifies that in Brazil social and traditional entrepreneurs face the same set of challenges despite the widespread belief of the opposite.

Competências operacionais em redes de manufatura: uma análise sob a perspectiva coevolucionária

Esta tese tem como objetivo principal investigar como ocorre a disseminação de competências operacionais entre matriz e unidades fabris de redes de manufatura. Este objetivo principal se desdobra em cinco objetivos secundários: (i) Definir o conceito de competência operacional; (ii) Identificar os possíveis fatores que influenciam a disseminação de competências operacionais em rede de manufatura sob a ótica de seus atores; (iii) Identificar as possíveis inter-relações entre esses fatores que possam favorecer a disseminação de competências operacionais em uma rede de manufatura, sob a percepção dos atores; (iv) Investigar e analisar como as organizações interagem para promover o reforço ou a criação de competências operacionais entre suas diversas unidades, observando sua dinâmica e a interação entre os atores; (v) Analisar como a combinação entre fatores internos (nível micro) e fatores externos (do ambiente competitivo) influenciam e são influenciados por essa dinâmica. Para tanto, apresenta-se uma pesquisa qualitativa no campo de Estratégia de Operações baseada na Teoria da Coevolução, dividida em dois estudos. O primeiro estudo, de cunho exploratório, procura identifica os antecedentes da disseminação de competências. Através da condução de um focus group e posteriormente entrevistas semi-estruturadas com Executivos de Operações, foi possível elencar os principais fatores que influenciam o processo de disseminação de competências. O segundo trabalho é um estudo de casos múltiplos, conduzido com 4 redes de manufatura. Pode-se observar que a coevolução das unidades fabris e disseminação de competências é um processo gradativo, possui fatores motivacionais cumulativos, envolve atores de dimensões distintas e com velocidade de absorção distintos. A partir dos achados, foi possível identificar que a maturidade da construção de competências operacionais evolui ao passo do nível de maturidade que a manufatura se encontra.

The effect of guia exame’s ratings on the brazilian fund industry: an analysis of net-worth flows

This paper infers the impact the publication “Guia Exame” (the guide) has on the Brazilian fund industry, more specifically on the ability the concerned funds develop on attracting new investment. The impact is measured using the event-study analysis based on the variation of net worth subsequently to the event of being rated, according to the methodology applied by the guide to rank the funds. We used five years of fund ratings according to Guia Exame (2000-2004) and analyzed the changes of these funds’ net worth. We also compared the event amongst different categories of funds. The results found confirm the expected effects according to star rankings and asset manager size in all years.

Cabinet composition and assessment of a multiparty presidential system

This doctoral dissertation provides a detailed analysis of the Brazilian cabinet according to the concepts of a multiparty presidential system. Appointing politicians as ministers is one of the most important coalition-building tools and has been widely used by minority presidents. This dissertation will therefore analyze the high-level Brazilian national bureaucracy between 1995 and 2014. It argues that the ministries – or departments – are not equal, and that allied parties therefore take into account the different characteristics of a ministry when demanding positions as a patronage strategy or for use as other kinds of political assets. After reviewing the literature on the theme, followed by a comparative analysis of the Brazilian, Chilean, Mexican, and Guatemalan cabinets, all the Brazilian ministries will be weighed and ranked on a scale that is able to measure their political importance and attractiveness. This rank takes into account variables such as the budgetary power, the ability to spend money according the ministers’ will, the ability to hire new employees, the ministries’ influence over other governmental agents such as companies, agencies, and so on, the ministers’ tenure in office. Finally, a proxy is provided that seeks to identify the normative power a department may hold. All of these characteristics will then be taken into account in considering the representatives’ opinion, thus helping to ascertain whether the cabinet appointment has been coalescent among the several parties that belong to the president’s coalition.