Is what you say what you do? Analyzing and comparing the effect of buyer-supplier relationship in the Brazilian and Chinese supplier selection criteria

Choosing properly and efficiently a supplier has been challenging practitioners and academics since 1960’s. Since then, countless studies had been performed and relevant changes in the business scenario were considered such as global sourcing, quality-orientation, just-in-time practices. It is almost consensus that quality should be the selection driver, however, some polemical findings questioned this general agreement. Therefore, one of the objectives of the study was to identify the supplier selection criteria and bring this discussion back again. Moreover, Dickson (1966) suggested existing business relationship as selection criterion, then it was reviewed the importance of business relationship for the company and noted a set of potential negative effects that could rise from it. By considering these side effects of relationship, this research aimed to investigate how the relationship could influence the supplier selection and how its harmful effects could affect the selection process. The impact of this phenomenon was investigated cross-nationally. The research strategy adopted was a controlled experiment via vignette combined with discrete choice analysis. The data collections were performed in China and Brazil. By examining the results, it could be drawn five major findings. First, when purchasers were asked to declare their supplier selection priorities, quality was stated as the most important independently of country and relationship. This result was consistent with diverse studies since 60’s. However, when purchasers were exposed to a multi-criteria trade-off situation, their actual selection priorities deviate from what they had declared. In the actual decision-making without influence of buyer-supplier relationship, Brazilian purchasers focused on price and Chinese buyers prioritized delivery then price. This observation reinforced some controversial prior studies of Verma & Pullman (1998) and Hirakubo & Kublin (1998). Second, through the introduction of the buyer-supplier relationship (operationalized via relational capital) in the supplier selection process, this research extended the existing studies and found that Brazilian buyers still focused on price. The relationship became just another criterion for supplier selection such as quality and delivery. However, from the Chinese sample, the results suggested that quality was totally discarded and the decision was majorly made through price and relationship. The third finding suggested that relational capital could legitimate the quality and sustainability of the supplier and replaces these selection criteria and made the decisional task less complex. Additionally, with the relational capital, the decision-makings were associated to few biases such as availability cognition, commitment, confirmatory and perceived biases. By analyzing the purchasers’ behavior, relational capital inducted buyers of both countries to relax in their purchasing requirements (quality, delivery and sustainability) leading to potential negative effects. In the Brazilian sample, the phenomenon of willing to pay a higher price for a lower quality offer demonstrated to be a potential counterproductive and suboptimal decision. Finally, the last finding was associated to the cultural effect on the buyers’ decisions. From the outcome, it is possible to observe that if a purchaser’s cultural background is more relation-oriented, the more he will tend to use relational capital as a decision heuristic, thus, the purchaser will be more susceptible to the potential relationship’s side effects

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.

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.

Forecasting accuracy and estimation uncertainty using VAR models with short- and long-term economic restrictions: a Monte-Carlo study

Using vector autoregressive (VAR) models and Monte-Carlo simulation methods we investigate the potential gains for forecasting accuracy and estimation uncertainty of two commonly used restrictions arising from economic relationships. The Örst reduces parameter space by imposing long-term restrictions on the behavior of economic variables as discussed by the literature on cointegration, and the second reduces parameter space by imposing short-term restrictions as discussed by the literature on serial-correlation common features (SCCF). Our simulations cover three important issues on model building, estimation, and forecasting. First, we examine the performance of standard and modiÖed information criteria in choosing lag length for cointegrated VARs with SCCF restrictions. Second, we provide a comparison of forecasting accuracy of Ötted VARs when only cointegration restrictions are imposed and when cointegration and SCCF restrictions are jointly imposed. Third, we propose a new estimation algorithm where short- and long-term restrictions interact to estimate the cointegrating and the cofeature spaces respectively. We have three basic results. First, ignoring SCCF restrictions has a high cost in terms of model selection, because standard information criteria chooses too frequently inconsistent models, with too small a lag length. Criteria selecting lag and rank simultaneously have a superior performance in this case. Second, this translates into a superior forecasting performance of the restricted VECM over the VECM, with important improvements in forecasting accuracy ñreaching more than 100% in extreme cases. Third, the new algorithm proposed here fares very well in terms of parameter estimation, even when we consider the estimation of long-term parameters, opening up the discussion of joint estimation of short- and long-term parameters in VAR models.

Terceirização em informática no Brasil: investigação sobre a situação da terceirização em informática no contexto brasileiro

The text relates an empirical investigation on Brazilian information systems and services outsourcing context, revealing some important characteristics about formerly unclear matter. The research analyses the reasoning for outsourcing, the implementation process, the partners selection criteria, the destination of internal technical personnel, the agreement writing process, the start prices and further revisions, the plans for the future, segments transferred to external partners, effective benefits and difficulties and major concerns about outsourcing.

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.

Unidades técnico-científicas da Polícia Federal: um estudo de caso do processo de descentralização da perícia criminal federal

Este estudo buscou identificar e analisar como foi planejado e executado o processo de descentralização da perícia criminal federal, bem assim, identificar a razão para os desvios havidos entre o planejamento e a implementação e as consequências advindas. Uma revisão da teoria precedeu a análise dos dados, obtidos através de pesquisa de campo constituída por oito entrevistas, sendo cinco entre os planejadores e executores do processo de descentralização, e três com os responsáveis por unidades descentralizadas. O planejamento do processo de descentralização foi realizado por equipes intermediárias do escalão dirigente do Departamento de Polícia Federal. Conforme levantamento empreendido por esses idealizadores, constatou-se uma alta demanda por assistência pericial em investigações conduzidas em cidades afastadas das capitais dos estados, onde residia o único centro forense disponível em cada unidade da federação. A distância do local da demanda para as capitais e a limitada capacidade de atendimento das unidades estaduais prevenia o atendimento tempestivo das requisições, situação que, por vezes, comprometia toda a eficácia da investigação policial. A par dessas constatações e tendo sido identificadas as principais especialidades requeridas, o volume de solicitações, a infraestrutura local disponível e outras características associadas à demanda e aos seus locais de origem, foram delimitados requisitos para a identificação de cidades que receberiam unidades técnico-científicas e delimitação das características dessas unidades. Os parâmetros fixados para dimensionar as unidades descentralizadas, como requisitos de infraestrutura, recursos humanos e equipamentos, acabaram por ser flexibilizados durante o processo de implementação devido à insuficiência de recursos financeiros para a implementação concebida. Como resultado, houve instalação de unidades incompletas; com corpo técnico carente das expertises requeridas; com infraestrutura física inadequada; em localidades não previstas; sem os laboratórios e equipamentos necessários. Os empecilhos indicados sinalizam que o plano foi estabelecido sem a análise precisa das forças e fraquezas, oportunidades e desafios que impactariam a sua execução. A ausência do envolvimento da alta administração da Polícia Federal pode explicar parte das deficiências encontradas no processo. Embora a descentralização tenha melhorado as condições para a atuação das equipes de investigação, diversas deficiências ainda precisam ser suprimidas para garantir melhor efetividade da assistência da perícia. Conclui-se pela necessidade de uma completa revisão do processo de descentralização da estrutura pericial, a fim de se identificar os ajustes necessários para o aprimoramento das condições de operação das unidades técnico-científicas descentralizadas.

Impact investing: portfolio company selection in Latin America

O documento analisa como investidores de impacto selecionar suas companhias de portfólio na América Latina e que critérios são avaliados no processo. Uma vez que praticamente ne-nhuma pesquisa sobre isso foi con conduzidos até à data, e desde que o modelo de processo de seleção aplicados em capital de risco não é dissemelhantes, foi adotado essa abordagem. Os resultados revelam que os investidores de impacto originar e avaliar negócios de uma for-ma semelhante a capitalistas de risco , mas que alguns critérios são ajustados e outros adicio-nados a fim de refletir o duplo objectivo de investimento de impacto. Os investidores de im-pacto podem originar ofertas passivamente, mas eles preferem procurar empreendimentos sociais de forma proativa: contatos pessoais, o acesso a redes e eventos do setor são cruciais neste contexto. Impacto Investidores considerando um investimento em pesquisa para a Amé-rica Latina inteira, empreendedores sociais honestos e confiáveis comprometidos com impacto social; empreendimentos sociais elegíveis devem ser rentáveis com potencial de escalabilidade; o produto deve ter um impacto social, ou seja, criar valor para o consumidor individual e para a comunidade em geral; tamanho do mercado e crescimento do mercado são fatores externos cruciais; e as características de negócio dependem de atitude de risco do investidor e as perspectivas de uma saída bem sucedida, tanto em termos financeiros e sociais. Os investi-dores de impacto também estão dispostos a dar apoio não financeiro antes de um investimen-to, se um empreendimento social, mostra alto potencial para atingir o seu objectivo dual.