Illegitimacy,paternal financial responsibility,and the 1834 Poor Law Commission Report: the myth of the old poor law and the making of the new

The new poor law's bastardy clauses were amongst the most contested of the 1834 Act, and their unpopularity led to their (partial) reversal by 1844. The issue of paternal financial responsibility for the maintenance of illegitimate children was central to the reforms, and this article uses the Rural and Town Queries to show how parishes could enforce this responsibility effectively. This evidence could have been used as an alternative model of reform; instead, the Poor Law Commissioners misrepresented the operation of the law and recommended the abolition of affiliation. Rooted in the writings of Malthus, their proposals proved ultimately impracticable.     

An index of growth due to depreciation*

Abstract. While factors such as inflation, technological change and growth often have been discussed in connection with the adequacy of provisions for depreciation under a historical cost model, there is another dimension to the capital maintenance problem and it concerns the multiplier effect of depreciation. When an amount equal to depreciation is reinvested, a firm's productive capacity tends to increase. Reinvestment of depreciation also increases a firm's financial capital if book depreciation is more accelerated than economic depreciation. Based on a model developed by Ijiri (1967), this paper derives an index of this growth due to depreciation. The index estimates a bias in conventional depreciation methods that has been overlooked in the literature on the subject. This bias has implications for inflation accounting because if conventional depreciation methods have a built-in growth bias, adjustments for inflation may be a type of double counting. A second implication mentioned concerns the bias in accounting rates of return. Résumé. Bien que des facteurs tels l'inflation, les changements technologiques et la croissance ont souvent été examinés à propos de la pertinence des provisions pour dépréciation dans le cadre du modèle au coût historique, un autre aspect du problème de préservation du capital subsiste et il concerne l'effet multiplicateur de l'amortissement. Lorsqu'un montant égal à l'amortissement est réinvesti, la capacité d'exploitation de la firme a tendance à s'accroître. Le réinvestissement de l'amortissement fait aussi augmenter le capital de la firme si l'amortissement comptable est plus accéléré que la dépréciation économique. En se basant sur un modèle élaboré par Ijiri (1967), cet article dérive un indice de cette croissance attribuable à l'amortissement. L'indice estime un biais des méthodes traditionnelles, qui a été négligé dans les recherches consacrées au sujet. Ce biais a des implications en comptabilité des effets de l'inflation, car si les méthodes d'amortissement traditionnelles comportent implicitement ce biais de croissance, les redressements relatifs à l'inflation peuvent être assimilés à un double comptage. Une deuxième conséquence est signalée, soit le biais relatif aux taux de rendement comptable.     

Benefits from U.S. Monetary Policy Experimentation in the Days of Samuelson and Solow and Lucas

A policy maker knows two models. One implies an exploitable inflation-unemployment trade-off, the other does not. The policy maker's prior probability over the two models is part of his state vector. Bayes' law converts the prior probability into a posterior probability and gives the policy maker an incentive to experiment. For models calibrated to U.S. data through the early 1960s, we compare the outcomes from two Bellman equations. The first tells the policy maker to "experiment and learn." The second tells him to "learn but don't experiment." In this way, we isolate a component of government policy that is due to experimentation and estimate the benefits from intentional experimentation. We interpret the Bellman equation that learns but does not intentionally experiment as an "anticipated utility" model and study how well its outcomes approximate those from the "experiment and learn" Bellman equation. The approximation is good. For our calibrations, the benefits from purposeful experimentation are small because random shocks are big enough to provide ample unintentional experimentation.     

Forecasts of earnings per share: Possible sources of analyst superiority and bias*

Abstract. Previous research has shown that analysts' forecasts of quarterly earnings per share (EPS) are more accurate than those of accepted time-series models. In addition, some previous research suggests that, on average, analysts' forecasts tend to be optimistic (i.e., biased). Two explanations for analysts' superiority have been proposed: (1) analysts use more recent information than can time-series models and (2) analysts use forecast-relevant information not included in the time-series of past earnings. This paper provides evidence on a third potential source of analyst superiority: the possibility that humans can use past earnings data to predict future earnings more accurately than can mechanical time-series models. We find that human judges do no worse than accepted time-series models when both use the same information set: namely, the series of past EPS figures. To date, little or no research has attempted to determine why analyst bias might exist. Still, some possible reasons have been forwarded. First, pessimistic forecasts or reports may hinder future efforts of the analyst or the analyst's employer to obtain information from the company being analyzed. Second, forecast data bases may suffer a selection bias if analysts tend to stop following those firms that they perceive as performing poorly. This study proposes, and provides evidence regarding, a third possible explanation for analyst bias: the use of judgmental heuristics by analysts. Many studies have shown that human predictions are often biased because of the use of such heuristics. We present evidence that suggests this may be the case for analysts' forecasts of earnings per share. Résumé. De précédents travaux de recherche ont démontré que les prévisions des analystes relatives au bénéfice par action (BPA) trimestriel sont plus exactes que celles que permettent d'obtenir les modèles reconnus basés sur les séries chronologiques. De plus, les résultats de certains travaux de recherche laissent croire qu'en moyenne, les prévisions des analystes tendent à être optimistes (c'est-à-dire biaisées). Deux explications à cette supériorité ont été proposées: 1) l'information que les analystes utilisent est plus récente que celles utilisées dans les modèles fondés sur les séries chronologiques et 2) les analystes utilisent de l'information pertinente aux prévisions qui ne figure pas dans les séries chronologiques relatives aux bénéfices passes. Les auteurs attribuent à un troisième facteur potentiel cette supériorité: la possibilité pour les humains d'utiliser les données relatives aux bénéfices passés pour prédire les bénéfices futurs de façon plus précise que ne le peuvent les modèles fondés sur les séries chronologiques. Ils en viennent à la conclusion que les humains obtiennent des résultats tout aussi efficaces que les modèles chronologiques reconnus lorsqu'ils utilisent un jeu de renseignements identique, soit les données historiques relatives au BPA. Jusqu'à maintenant, peu de chercheurs, sinon aucun, ont tenté de déterminer à quoi tiendrait l'existence d'un biais chez l'analyste. Malgré tout, certaines explications possibles ont été proposées. Premièrement, les prévisions ou les rapports pessimistes peuvent faire obstacle aux efforts futurs de l'analyste ou de son employeur pour obtenir de l'information de la société faisant l'objet de l'analyse. Deuxièmement, les bases de données servant à la prévision peuvent être entachées d'un biais de sélection si les analystes ont tendance à cesser de suivre les entreprises qui leur semblent afficher une piètre performance. Les auteurs proposent et attestent une troisième explication possible du biais de l'analyste: l'utilisation de méthodes heuristiques fondées sur le jugement. De nombreuses études ont démontré que les prédictions humaines sont souvent biaisées par suite de l'utilisation de ces méthodes heuristiques. Les auteurs apportent des arguments qui permettent de croire que ce pourrait être le cas des prévisions des analystes du bénéfice par action.     

An Investigation of Transactions Data for NYSE Stocks

Using transactions data, the behavior of returns and characteristics of trades at the micro level is examined. A minute-by-minute market return series is formed and tested for normality and autocorrelation. Evidence of differences in return distributions is found among overnight trades, trades during the first 30 minutes following the market opening, trades at the close, and trades during the remainder of the day. The latter distribution is found to be normal. Unusually high returns and standard deviations of returns are found at the beginning and the end of the trading day. When the beginning-and end-of-the-day effects are omitted, autocorrelation in the market return series is reduced substantially. A number of patterns in trading are reported.     

Textile marketing: a status report

This exploratory study investigated the status of textile marketing in the United States by (a) examining the textile industry's use of effective marketing techniques, and (b) identifying common problems and needed improvements in textile marketing. The procedure followed these steps: (a) effective marketing techniques were identified, (b) interviews were conducted with nine textile executives and four individuals representing the United States textile industry at large, and (c) the respondents' statements about textile marketing practices were analysed for evidence of effective marketing techniques, common textile marketing problems and needed inprovements in textile marketing. The results indicated that only five of the thirteen respondents described textile firms that were using effective marketing techniques, but some textile firms were using effective marketing techniques and this should be an incentive for other textile firms. Several common problems and needed improvements in textile marketing were also identified. Because of the small sample size, the open-ended questions, and the subjective analysis of the respondents' statements, this study must be regarded as exploratory. However, representative statements from the respondents are presented and these statements are informative about textile marketing practices.