The Use of Different Endorser Types in Advertising: A Content Analysis of Magazine Advertisements

Most of the literature assumes that endorsements, particularly by celebrities, are a frequently used advertising strategy. However, no study has yet investigated the use of the different endorser types identified by academic literature. This study seeks to close this research gap by analyzing German print advertisements. It finds that endorsement strategy in general is used much less than academic literature assumes, and that the relative significance of the different endorser types is incongruent to expectations. Moreover, the data suggest that, contrary to the literature's assumptions, credibility is not the most important underlying construct for endorsement advertisements, the endorser type used is frequently determined by the product category that is being advertised, and campaigns based on authenticity and similarity are gaining considerable importance in advertising practice.     

The rise and fall of public sector plant breeding in the United Kingdom: a causal chain model of basic and applied research and diffusion

This paper examines the barley and wheat breeding programmes of the Plant Breeding Institute (PBI), which was the most successful public plant breeding institute in the UK, until privatization in 1987. The PBI's shares in barley and wheat seed sales are explained, showing that the success with barley was largely a matter of serendipity, whereas the wheat programme followed a more normal pattern. For wheat, the causal chain, or recursive, model decomposes the well-documented link between research expenditures and increases in agricultural productivity into three stages. These are the effects of R&D expenditures on basic research output, measured by publications, the effect of publications and applied R&D expenditures on trial plot yields, and the diffusion of the trial plot technologies, which raises yields on farms. Applying the model to the FBI's wheat varieties allows estimation of the lag structures. In contrast to the results for aggregate agricultural research, for a single plant breeding programme alone there is a considerable lead time before there is any response, followed by a lag distribution only a few years long. The returns to the R&D investments are calculated from the causal chain model, from single equation estimates and by evaluating the yield advantage of the PBI varieties. All three approaches give consistent results, which show that the returns to barley and wheat alone were sufficient to support the entire PBI budget and still give rates of return to applied research of between 14 and 25%. The return to the basic science expenditures of the John Innes Institute has a lower bound of 17%, but must have been even higher than for the PBI if the other Institutes were taken into account. The paper concludes by commenting on the effects of the privatization of the PBI.     

The impact of seed industry concentration on innovation: a study of US biotech market leaders

Agricultural research drives increases in agricultural productivity, and the number of private agricultural input firms has been declining. The empirical relationship between the number of firms doing applied biotechnology crop research and the amount of research output they produce is investigated in a research profit function model. Increases in seed industry concentration have reduced biotech research intensity in the United States in the 1990s. Concentration and research are simultaneously determined and are influenced by the appropriability of research results and the state of technological opportunity.     

An error correction model of induced innovation in UK agriculture

Cointegration techniques are applied to a model of induced innovation based on the two-stage Constant Elasticity of Substitution (CES) production function. This approach results in direct tests of the inducement hypothesis, which are applied to agricultural data for the United Kingdom from 1953 to 2000. The time series properties of the variables are checked, cointegration is established and an Error Correction Model (ECM) constructed, which attempts to separate factor substitution from technological change. Finally, the ECM formulation is subjected to causality tests, which show that the factor price ratio for chemicals and land is Granger-prior to the factor-saving bias of technological change. However, long-run relative prices are not causally prior to the machinery/labour ratio. This results from perturbations in the user cost of machinery, caused by oil price shocks. Thus, the Induced Innovation Hypothesis (IIH) may explain long-run transformations like the mechanical and fertilizer revolutions that dominated the twentieth century, but not reflect short-run price volatility.     

Evaluating research and education performance in Indian agricultural development

India's agricultural research spending has long been regionally uneven. Regional research intensity ratios, which account for size differences, indicate research spending has consistently favored southern and western states over northern, central, and eastern ones. Farm production patterns have, however, changed in recent years and regional output growth is being driven by new commodity mixes. In this article, we ask which region had the highest factor productivity growth and rate of return to investments in public agricultural research and higher education. Our analysis relies on a 1980–2008 Indian agricultural production and policy data set together with a dual heteroscedastic production frontier to decompose total factor productivity (TFP) growth into formal technical progress and efficiency elements. The model's regional flexibility affords region‐to‐region comparison of multiple research return rates, TFP growth, and the elements influencing them. Regardless of return‐rate measure or allocation scenario evaluated, the North has enjoyed the highest return to research spending, and the Central and East the lowest. Factor productivity growth has however been strongest in the South, primarily on account of efficiency gains. Overall, though, the technical progress and productivity growth easily attributable to government‐supported research has accounted for about one‐quarter of the sector's TFP growth.     

Estimating the Value of an Early-Warning System

An early-warning system generates economic value to the extent that it improves decision making. The value of the information hinges on the degree to which a timely response, aided by warnings, facilitates successful damage mitigation. USDA's Coordinated Framework for Soybean Rust includes a network of sentinel soybean plots and wild kudzu stands monitored by extension agents for the presence of soybean rust, a potentially recurring threat to the U.S. soybean crop since 2005. The linchpin in this early-warning system is a website that provides near real-time, county-level information on the location of the disease. We consider factors that may influence information value.     

Efficiency effects of agricultural economics research in the United States

Allocations of research funds across programs are often made for efficiency reasons. Social science research is shown to have small, lagged but significant effects on U.S. agricultural efficiency when public agricultural R&D and extension are simultaneously taken into account. Farm management and marketing research variables are used to explain variations in estimates of allocative and technical efficiency using a Bayesian approach that incorporates stylized facts concerning lagged research impacts in a way that is less restrictive than popular polynomial distributed lags. Results are reported in terms of means and standard deviations of estimated probability distributions of parameters and long‐run total multipliers. Extension is estimated to have a greater impact on both allocative and technical efficiency than either R&D or social science research.     

What is the Value of Agricultural Economics Research?

The output of agricultural economics research is information, much of it aimed at designing or improving institutions. Bayesian decision theory and economic surplus analysis have been suggested as possible approaches to evaluate that information. This article takes a critical look at the strengths and weaknesses of combining those approaches for empirical evaluation of agricultural economics research. It presents three case studies, utilizing prior and posterior probabilities elicited from key decision makers. Direct application of the probabilities to a simple set of states and actions is best suited to situations involving a single policy-making center, or a consensus decision-making process.