An ordering of measures of the welfare cost of inflation in economies with interest-bearing deposits

This paper builds on Lucas (2000) and on Cysne (2003) to derive and order six alternative measures of the welfare costs of inflation (five of which already existing in the literature) for any vector of opportunity costs. The ordering of the functions is carried out for economies with or without interestbearing deposits. We provide examples and closed-form solutions for the log-log money demand both in the unidimensional and in the multidimensional setting (when interest-bearing monies are present). An estimate of the maximum relative error a researcher can incur when using any particular measure is also provided.

Measures of the welfare cost of inflation: a complete ordering

This paper presents three contributions to the literature on the welfare cost of ináation. First, it introduces a new sensible way of measuring this cost - that of a compensating variation in consumption or income, instead of the equivalent variation notion that has been extensively used in empirical and theoretical research during the past fiftt years. We Önd this new measure to be interestingly related to the proxy measure of the shopping-time welfare cost of ináation introduced by Simonsen and Cysne (2001). Secondly, it discusses for which money-demand functions this and the shopping-time measure can be evaluated in an economically meaningful way. And, last but not least, it completely orders a comprehensive set of measures of the welfare cost of ináation for these money-demand specification. All of our results are extended to an economy in which there are many types of monies present, and are illustrated with the log-log money-demand specification.

Fundamentos em processamento de linguagem natural: uma proposta para extração de bigramas

É senso comum que o texto escrito é uma importante forma de registrar as informações e que atualmente grande parte desse conteúdo informacional está disponível em meio digital. Entretanto, de maneira geral, os computadores lidam com o texto como sendo uma cadeia de caracteres que não têm nenhum significado. A área de Processamento de Linguagem Natural (PLN) vem se empenhando em extrair significados do texto. Nesse sentido este trabalho apresenta uma revisão desse tema e propõe um método automatizado que utiliza uma heurística determinística denominada Heudet que visa extrair bigramas do texto. A meta é extrair o significado do texto através de um conjunto de expressões multipalavras identificadas. Os resultados obtidos foram melhores se comparados com aqueles que utilizam-se das técnicas de medidas de associação estatística obtidas pelo software Ngram Statistics Package (NSP).

Identification and estimation of interventions using changes in inequality measures

This paper presents semiparametric estimators of changes in inequality measures of a dependent variable distribution taking into account the possible changes on the distributions of covariates. When we do not impose parametric assumptions on the conditional distribution of the dependent variable given covariates, this problem becomes equivalent to estimation of distributional impacts of interventions (treatment) when selection to the program is based on observable characteristics. The distributional impacts of a treatment will be calculated as differences in inequality measures of the potential outcomes of receiving and not receiving the treatment. These differences are called here Inequality Treatment Effects (ITE). The estimation procedure involves a first non-parametric step in which the probability of receiving treatment given covariates, the propensity-score, is estimated. Using the inverse probability weighting method to estimate parameters of the marginal distribution of potential outcomes, in the second step weighted sample versions of inequality measures are computed. Root-N consistency, asymptotic normality and semiparametric efficiency are shown for the semiparametric estimators proposed. A Monte Carlo exercise is performed to investigate the behavior in finite samples of the estimator derived in the paper. We also apply our method to the evaluation of a job training program.