Measuring the impact of R&;D on Productivity from a Econometric Time Series Perspective

In this paper we argue that the standard sequential reduction approach to modelling dynamic relationships may be sub-optimal when long lag lengths are required and especially when the intermediate lags may be less important. A flexible model search approach is adopted using the insights of Bayesian Model probabilities, and new information criteria based on forecasting performance. This approach is facilitated by exploiting Genetic Algorithms. Using data on U.K. and U.S. agriculture the bivariate time series relationship between R&D expenditure and productivity is analysed. Long lags are found in the relationship between R&D expenditures and productivity in the U.K. and in the U.S. which remain undiscovered when using the orthodox approach. This finding is of particular importance in the debate on the optimal level of public R&D funding.JEL Classification: C22, C51, Q16     

Political contributions and analyst behavior

We show that the personal traits of analysts, as revealed by their political donations, influence their forecasting behavior and stock prices. Analysts who contribute primarily to the Republican Party adopt a more conservative forecasting style. Their earnings forecast revisions are less likely to deviate from the forecasts of other analysts and are less likely to be bold. Their stock recommendations also contain more modest upgrades and downgrades. Overall, these analysts produce better quality research, which is recognized and rewarded by their employers, institutional investors, and the media. Stock market participants, however, do not fully recognize their superior ability as the market reaction following revisions by these analysts is weaker.     

Traffic lights and food choice: A choice experiment examining the relationship between nutritional food labels and price

In this paper we investigate how consumers respond to the UK nutritional food label Traffic Light System (TLS). Employing a choice experiment (CE) we find that consumers appear to behave in a manner consistent with our expectations regarding the impact of the TLS. We identify a strong preference on the part of respondents to avoid a basket of goods containing a mix of foods with any “Red” lights. In addition, we find that consumers have a hierarchy of importance in terms of perception of the various nutrients examined and there are clear behavioural differences associated with particular socio-economic characteristics confirming early research on the use of nutrition labels. Overall our results indicate significant heterogeneity in the attitudes and responses of consumers to the TLS nutritional food labels within and across socio-economic strata.     

One Country,Two Prices? A Study of the Deflationary Effect of Price Convergence on Hong Kong*

Consumer prices in Hong Kong at the time of writing have declined by 15 percent from the peak recorded in 1998. We investigate the deflationary impact on Hong Kong of price convergence with the Mainland China, using 1990–2001 annual data on commodity prices in the former and in major cities of the latter. We find evidence of price convergence between the two economies over the past decade. Furthermore, price convergence is estimated to have accounted for one‐fifth of the deflation in Hong Kong. The results suggest that a significant portion of the deflation in Hong Kong is attributable to a process of structural adjustment due to growing economic integration with the Mainland.     

Bayesian Estimation and Selection of Nonlinear Vector Error Correction Models: The Case of the Sugar-Ethanol-Oil Nexus in Brazil

Nonlinear adjustment toward long-run price equilibrium relationships in the sugar-ethanol-oil nexus in Brazil is examined. We develop generalized bivariate error correction models that allow for cointegration between sugar, ethanol, and oil prices, where dynamic adjustments are potentially nonlinear functions of the disequilibrium errors. A range of models are estimated using Bayesian Monte Carlo Markov Chain algorithms and compared using Bayesian model selection methods. The results suggest that the long-run drivers of Brazilian sugar prices are oil prices and that there are nonlinearities in the adjustment processes of sugar and ethanol prices to oil price but linear adjustment between ethanol and sugar prices.     

Stochastic Biases in Technical Change in U.S. Agriculture: A Bootstrap Approach

Having argued that the modeling of technical change as a smooth deterministic function of time is likely to misrepresent the true nature of technical change, this paper reexamines biased technical change in U.S. agriculture using a system of share equations with unobserved components errors, with technology treated as a stochastic unobserved variable. Employing data to represent the aggregate output and input of the U.S. agricultural sector over the period 1947–94, significant factor biases were found that appear to be linearly independent and do not appear to be smooth and deterministic. Technical change in U.S. agriculture appears to have been biased toward saving expenditure on labor at the expense of expenditure on intermediate inputs, with some small saving on the expenditure on capital inputs over the entire period 1947‐94. The paper also employs a bootstrapping approach in order to obtain finite sample tests with approximately the correct size under less stringent assumptions about the data generating process than assumed by maximum likelihood (ML) based approaches. Using these finite sample values significantly alters the conclusions reached regarding the nature of technical change. Après avoir démontré que la modélisation du changement technique par une fonction lissée déterministe du temps peut ne pas représenter correctement sa vraie nature, cet papier re‐examine le biais du changement technique dans l'agriculture américaine à partir d'un systè d'équations de parts avec des erreurs non observées et une technologie traitée comme une variable stochastique non observée. A partir de données représentant la production et les intrants agrégés dans le secteur agricole américain sur la période 1947–1994, nous constatons que les biais significatifs sont indépendants linéairement et qui ne sont pas des fonctions déterministes lissées du temps. Le changement technique dans l'agriculture américaine est biaisé en faveur des réductions de dépenses de travail aux dépends des dépenses sur les intrants intermédiaires et montre quelques économies sur les dépenses de capital sur la période 1947‐1994. L'emploi des techniques de bootstrapping permet d'obtenir des tests sur échantillons finis avec des hypothèses moins exigeantes que celles imposées par les approches de maximum de vraisemblance. Les conclusions obtenues à partir de ces tests sont significativement différentes que celles obtenues par les méthodes traditionnelles concernant le changement technique.     

Managers’ Unethical Fraudulent Financial Reporting: The Effect of Control Strength and Control Framing

In response to numerous recent cases involving materially misstated financial information arising from fraudulent financial reporting, companies, auditors, and academics have increased their focus on strengthening internal controls as a means of deterring such unethical behaviors. However, prior research suggests that stronger controls may actually exacerbate the very opportunistic behavior the controls are intended to curb. The current study investigates whether the efficacy of an implemented control is conditioned on not only the strength of the control (weaker or stronger), but also on how the firm frames the purpose for implementing the control (e.g., monitoring or coordinating). A monitoring purpose frames controls as reducing managers’ opportunities to engage in self-interested behavior, while a coordinating purpose frames controls as facilitating coordination between the firm and its managers. We posit that the efficacy of stronger controls to reduce unethical fraudulent reporting depends on the control frame. Using an experiment, this study investigates the interactive effect of control strength and control frame on managers’ fraudulent reporting decisions. As predicted, our results show that when controls are framed for monitoring purposes, stronger controls result in less fraudulent reporting than weaker controls. Conversely, when controls are framed for coordinating purposes, stronger controls result in more fraudulent reporting than weaker controls. Our results suggest that an inconsistency between the firm’s choice of the control strength and the control frame reduces the efficacy of the implemented control to curb unethical reporting behaviors. Furthermore, supplemental analysis shows that managers’ rationalization helps explain the interactive effect of control strength and communicated control purpose on fraudulent reporting.     

Measuring productivity growth when technological change is biased–a new index and an application to UK agriculture

Productivity growth is conventionally measured by indices representing discreet approximations of the Divisia TEP index under the assumption that technological change is Hicks-neutral. When this assumption is violated, these indices are no longer meaningful because they conflate the effects of factor accumulation and technological change. We propose a way of adjusting the conventional TFP index that solves this problem. The method adopts a latent variable approach to the measurement of technical change biases that provides a simple means of correcting product and factor shares in the standard Tornqvist-Theil TFP index. An application to UK agriculture over the period 1953–2000 demonstrates that technical progress is strongly biased. The implications of that bias for productivity measurement are shown to be very large, with the conventional TFP index severely underestimating productivity growth. The result is explained primarily by the fact that technological change has favoured the rapidly accumulating factors against labour, the factor leaving the sector.     

Application of a double bootstrap to investigation of determinants of technical efficiency of farms in Central Europe

The paper provides one of the first applications of the double bootstrap procedure (Simar and Wilson 2007) in a two-stage estimation of the effect of environmental variables on non-parametric estimates of technical efficiency. This procedure enables consistent inference within models explaining efficiency scores, while simultaneously producing standard errors and confidence intervals for these efficiency scores. The application is to 88 livestock and 256 crop farms in the Czech Republic, split into individual and corporate.