Lima

Using a field experiment eliciting the risk preferences of 490 9 th and 11 th grade students from a variety of school environments, we examine various factors influencing the development of these risk preferences. In addition to factors previously considered by economists (gender, ethnicity, height, and parental education) we also evaluate cognitive (proxied by math literacy) and emotional (proxied by patience and planning ability) development theories. There is substantially stronger support for the variables typically considered by economists; consistent with prior work we find that girls are more risk averse while tall and nonwhites individuals are more risk tolerant. Next, the impact of school characteristics on the development of risk preferences is examined. Two effects emerge: a peer effect and a quality effect. For the peer effect, individuals who are in a school with a higher percentage of students on free or reduced lunches are significantly more risk averse than those with a lower percentage of students from low-income families. For the quality effect, individuals in schools that have smaller class sizes and a higher percentage of educators with advanced degrees have more moderate levels of risk aversion. Further, school characteristics only influence the 11 th graders in the sample-lending some support to a causal argument.

This paper employs a nation-wide sample of supermarket scanner data to estimate a large brand-level demand system for beer in the U.S. using the Distance Metric method of Pinkse, Slade and Brett [Pinkse, J., Slade, M., Brett, C., 2002. Spatial price competition: a semiparametric approach. Econometrica 70, . Unlike previous studies, this work estimates the own-and cross-advertising elasticities in addition to price elasticities. Positive and negative cross-advertising elasticities imply the presence of both cooperative and predatory effects of advertising expenditures across brands; however, the former effect appears to dominate suggesting that advertising increases the overall demand for beer. We discuss the implications of these results in this industry.

Es wird eine Simulation des anaeroben Prozesses in Biogasanlagen beschrieben, die es erlaubt den Prozess für den Einsatz verschiedener realer Substrate zu optimieren. Als Basis zur Modellierung wird das ADM1-Modell (Anaerobic Digestion Model No. 1) verwendet. Es wurden Batch-Versuche mit verschiedenen Substraten sowie Experimente in einem kontinuierlichen Laborreaktor durchgeführt. Anhand der experimentellen Ergebnisse erfolgten eine Parametrisierung und Modifikationen im Modell. Es zeigte sich, dass eine Unterteilung des Substrates in verschieden schnell abbaubare Klassen zu einer guten Übereinbestimmung zwischen der Simulation des anaeroben Abbaus und den experimentellen Ergebnissen führt. A simulation of the anaerobic process of a biogas production for different substrates was realized. The simulation was based on the Anaerobic Digestion Model No. 1 (ADM1). The experimental work comprehends batch-experiments and experiments in a continuous stirred-tank reactor at lab scale with different substrates used in a biogas production. The comparison between the experiments and the simulations of the process leads to a modification in ADM1. Furthermore a classification of substrates was developed according to their biodegradability to meet the fractions of the ADM1 simulation.

Here, we present the results of lab-scale experiments conducted in a batch mode to determine the biogas yield of lipid-rich waste and corn silage under the effect of stirring. Further semi-continuous experiments were carried out for the lipid-rich waste with/without stirring. Additionally, it was analyzed how the starter used for the batch experiment influences the digestion process. The results showed a significant stirring effect on the anaerobic digestion only when seed sludge from a biogas plant was used as a starter. In this case, the experiments without stirring yielded only about 50% of the expected biogas for the investigated substrates. The addition of manure slurry to the batch reactor as part of the starter improved the biogas production. The more diluted media in the reactor allowed a better contact between the bacteria and the substrates making stirring not necessary.

A new strategy for matrix converters which allows optimal control of source and load currents is presented in this paper. This method uses the commutation state of the converter in the subsequent sampling time, according to an optimization algorithm given by the discrete system model and a simple cost function. The control goals include regulation of output current using an arbitrary reference and good tracking of the source current to its reference, to achieve a sinusoidal waveform. Experimental results from a 7.5 kW prototype support the theoretical development.

This study utilizes a brand-level dataset that captures a unique natural experiment, a 100% increase in the excise tax, to evaluate different pricing models in the U.S. beer industry. To assess the plausibility of different models, the increase in marginal cost resulting from the tax increase is exploited: observed prices in the post-increase period are compared to the prices that should be observed under various pricing models. Three types of models are analyzed: Bertrand-Nash, leadership, and collusion. Results indicate that extreme cases of collusion can be confidently ruled out while several models may explain the observed prices equally well.

Much recent innovation in teaching economics has focused around active learning strategies, which are often difficult or impossible to implement in large classes. We have developed a system that uses handheld devices and wireless technology to facilitate interactive learning in large classes by putting technology in the hands of the students during class. The Wireless Interactive Teaching System (WITS) consists of handheld wireless devices, a laptop server, and proprietary software. Students use the WITS system to trade in markets, play standard economics games, take multiple choice quizzes, and communicate with the instructor during class. This paper reports results of a controlled experiment to test the effectiveness of the WITS system using two 80-person principles of economics classes. Student who used the WITS system earned final grades that averaged 7 points higher than the control class, adjusting for other important influences on grades such as demographics, ability and experience. The impact on learning is highest for freshmen and women students, groups who often struggle with introductory economics, and lowest for male seniors, who, in our sample, tend to be engineering majors. Teaching evaluations are also significantly higher in the experimental class.

Multiphase (more than three phases) power electronic converters are required mainly for feeding variable-speed multiphase drive systems. This paper presents one such solution by using a direct ac-ac converter that can be used to supply a nine-phase drive system. The input is a fixed-voltage and fixed-frequency three-phase input, and the output is a variable-voltage and variable-frequency nine-phase output. A simple pulsewidth-modulation technique is developed for the proposed ac-ac converter named as a nonsquare three-to-nine-phase matrix-converter configuration. The developed modulation technique is based on the comparison of a high-frequency carrier signal with the duty ratios. Although the carrier-based scheme is widely employed for the control of back-to-back converters, it has recently been used for controlling a three-to-three-phase matrix converter. This concept is extended in this paper for controlling a three-to-nine-phase matrix converter. With the two techniques that are proposed, one outputs 0.75 of the input magnitude and the other outputs reach 0.762 of the input. This is the maximum value of the output voltage in the linear modulation range that can be achieved in this configuration of the matrix converter. The viability of the proposed control techniques is proved analytically through simulation and an experimental approach.

We consider a model of vertical competition where downstream firms (retailers) purchase an upstream input from a monopolist and are able to differentiate from each other in terms of quality. Our primary focus is to study the effects of introducing a large retailer, such as a Wal-Mart Supercenter, that is able to lower wholesale prices (i.e. buyer market power). We obtain two main results. First, the store with no buyer market power responds to the presence of the large retailer by increasing its quality, a finding that is consistent with recent efforts by traditional retailers to enhance shoppers' buying experience (i.e. quality). Second, the presence of a large retailer causes consumer welfare to increase. There are, however, two reasons for the increase in consumer welfare: consumers gain from the large retailer's low price (because the upstream discount is partially passed on to the retail price) as well as from the high quality level offered by the traditional retailer. Contrary to the conventional wisdom most of the consumer welfare gains seem due to the latter. The intuition for this result is that price competition softens substantially as a result of firms' quality differentiation. We also investigate the effects of buyer market power on retail and wholesale prices as well as on producer welfare.

This paper analyzes the degree of market power in the U.S. brewing industry as measured by the closeness between the observed pricing behavior of …rms and the equilibrium prices predicted by various pricing models: Bertrand-Nash, leadership, and collusion. Price leadership focuses on the largest U.S. beer producer Anheuser-Busch and its heavily marketed brand Budweiser whereas collusion focuses on the three largest brewers. Results indicate that Bertrand-Nash predicts the pricing behavior of …rms more closely than other models. Concerns about non-competitive pricing of the forms studied here should hence be low in this industry. Despite its closeness to the observed pricing behavior, Bertrand-Nash under-predicts prices of more price-elastic brands and over-predicts prices of less price-elastic brands.

This paper employs a nation-wide sample of supermarket scanner data to estimate a large brandlevel demand system for beer in the U.S. Unlike previous studies, this work estimates the ownand cross-advertising elasticities in addition to price elasticities. The dimensionality problem is solved with the Distance Metric method of Pinkse, Slade and Brett and the demand model follows the flexible Almost Ideal demand system. While price elasticities are consistent with previous results, positive and negative cross-advertising elasticities imply the presence of both cooperative and predatory effects of advertising expenditures across brands; however, the former effect appears to dominate suggesting that advertising increases the overall demand for beer.

We conduct Monte Carlo experiments to investigate the biases of assuming a misspecified demand model. We study continuous models (linear, log-linear and AIDS), and discrete choice models (logit) in the context of differentiated products and aggregate data. Estimating demand with the ‘wrong’ model yields varying degrees of bias in estimated elasticities, but the logit model can yield unbiased estimates for a certain size of the assumed market potential. Merger simulations confirm the key importance of market potential in logit estimation suggesting that a discrete choice model may be preferable even when the discreteness of the purchase decision is questionable.

This paper presents a nite control set model predictive control strategy with a prediction horizon of one sample time to control the three-phase four-leg neutral-point-clamped (NPC) inverter with an output LC lter. The four-leg NPC converter is developed to deliver power to the unbalanced/nonlinear three-phase loads and it can produce three output voltages independently with one additional leg. The proposed predictive method uses the discrete model of the inverter and load to predict the future load and capacitor voltage behavior for each valid switching state of the converter. The control method chooses a state which generates minimum error between the output voltages and their references and as well as between the capacitor voltages. The feasibility of the proposed predictive control scheme is veried by computer simulations, showing a good performance and the capacity to compensate disturbances while maintaining balancing of the dc-link capacitor voltages.

The logit model is the most popular tool in estimating demand for differentiated products. In this model, the outside good plays a crucial role because it allows consumers to stop buying the differentiated good altogether if all brands simultaneously become less attractive (for example if a simultaneous price increase occurs). But practitioners lack data on the outside good when only aggregate data is available. The currently accepted procedure is to assume a "market potential" that implicitly defines the size of the outside good (i.e. the number of consumers who considered the product but did not purchase); in practice, this means that an endogenous quantity is approximated by a reasonable guess thereby introducing the possibility of an additional source of error and, most importantly, bias. We provide two contributions in this paper. First, we show that structural parameters can be substantially biased when the assumed market potential does not approximate the outside option correctly. Second, we show how to use panel data techniques to produce unbiased structural estimates by treating the market potential as a fixed effect (known as a "correlated random effect" in the non-linear panel data literature). We explore three possible solutions: a) controlling for the unobservable with market fixed effects, b) specifying the unobservable to be a linear function of the (average) product characteristics, and c) a "demeaned" regression approach. Solution a) is feasible (and preferable) when the number of goods is large relative to the number of markets, whereas b) and c) are attractive when the number of markets is too large. Importantly, we find that all three solutions are nearly as effective in removing the bias. We demonstrate our two contributions in the simple and random coefficients versions of logit via Monte Carlo experiments and with data from the automobile and breakfast cereals markets.

An aqueous-enzymatic extraction process of plum kernel oil was investigated on a laboratory scale, varying several processing parameters, with main emphasis on the oil yield. Efficient recovery of oil was related to three operations: pretreatment, enzymatic reaction and separation of oil. Maximum oil yield of about 70% (estimated by the Soxhler method) was obtained at an enzyme concentration of 0.So/o, extraction temperature of 45"C, pH 4.5, treatment time of 2 h and dilution ratio of 1 : 4. The aqueous-enzymatic extraction did not have any determining effect on the fatty acid composition, tocopherol composition, iodine value and saponification value. The free fatty acid content was higher, while the phosphatide content and peroxide value were lower in the oil extracted by the aqueous-enzymatic process as compared to the Soxhler extracted samples.

This paper employs a nation-wide sample of supermarket scanner data to estimate a large brandlevel demand system for beer in the U.S. Unlike previous studies, this work estimates the ownand cross-advertising elasticities in addition to price elasticities. The dimensionality problem is solved with the Distance Metric method of Pinkse, Slade and Brett and the demand model follows the flexible Almost Ideal demand system. While price elasticities are consistent with previous results, positive and negative cross-advertising elasticities imply the presence of both cooperative and predatory effects of advertising expenditures across brands; however, the former effect appears to dominate suggesting that advertising increases the overall demand for beer.

Much recent innovation in teaching economics has focused around active learning strategies, which are often difficult or impossible to implement in large classes. We have developed a system that uses handheld devices and wireless technology to facilitate interactive learning in large classes by putting technology in the hands of the students during class. The Wireless Interactive Teaching System (WITS) consists of handheld wireless devices, a laptop server, and proprietary software. Students use the WITS system to trade in markets, play standard economics games, take multiple choice quizzes, and communicate with the instructor during class. This paper reports results of a controlled experiment to test the effectiveness of the WITS system using two 80-person principles of economics classes. Student who used the WITS system earned final grades that averaged 7 points higher than the control class, adjusting for other important influences on grades such as demographics, ability and experience. The impact on learning is highest for freshmen and women students, groups who often struggle with introductory economics, and lowest for male seniors, who, in our sample, tend to be engineering majors. Teaching evaluations are also significantly higher in the experimental class.