985 resultados para Information Economics


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The information society thesis, according to which economically advanced nations are undergoing transformation into post-industrial, information-based societies, can, with caveats, be taken as a premise. Essentially empirical or predictive, this influential set of claims quickly gives rise to major normative issues. The paper asks how, as part of a prospective normative theory of the information society, information may be shown to contribute to social goals in general and social welfare in particular. Given the diverse range of referents of the term 'information' in the context of the information society debate, the paper focuses on news as a form of information whose communication is widely held to be important to society. The problem is how to quantify or otherwise prove this intuition. It is suggested that a fusion of welfare economics and the economics of information may yield a solution. The paper is designed to be exploratory, offering a potential line of inquiry for the future research and policy agenda of information society studies.

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I investigate the effects of information frictions in price setting decisions. I show that firms' output prices and wages are less sensitive to aggregate economic conditions when firms and workers cannot perfectly understand (or know) the aggregate state of the economy. Prices and wages respond with a lag to aggregate innovations because agents learn slowly about those changes, and this delayed adjustment in prices makes output and unemployment more sensitive to aggregate shocks. In the first chapter of this dissertation, I show that workers' noisy information about the state of the economy help us to explain why real wages are sluggish. In the context of a search and matching model, wages do not immediately respond to a positive aggregate shock because workers do not (yet) have enough information to demand higher wages. This increases firms' incentives to post more vacancies, and it makes unemployment volatile and sensitive to aggregate shocks. This mechanism is robust to two major criticisms of existing theories of sluggish wages and volatile unemployment: the flexibility of wages for new hires and the cyclicality of the opportunity cost of employment. Calibrated to U.S. data, the model explains 60% of the overall unemployment volatility. Consistent with empirical evidence, the response of unemployment to TFP shocks predicted by my model is large, hump-shaped, and peaks one year after the TFP shock, while the response of the aggregate wage is weak and delayed, peaking after two years. In the second chapter of this dissertation, I study the role of information frictions and inventories in firms' price setting decisions in the context of a monetary model. In this model, intermediate goods firms accumulate output inventories, observe aggregate variables with one period lag, and observe their nominal input prices and demand at all times. Firms face idiosyncratic shocks and cannot perfectly infer the state of nature. After a contractionary nominal shock, nominal input prices go down, and firms accumulate inventories because they perceive some positive probability that the nominal price decline is due to a good productivity shock. This prevents firms' prices from decreasing and makes current profits, households' income, and aggregate demand go down. According to my model simulations, a 1% decrease in the money growth rate causes output to decline 0.17% in the first quarter and 0.38% in the second followed by a slow recovery to the steady state. Contractionary nominal shocks also have significant effects on total investment, which remains 1% below the steady state for the first 6 quarters.

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In this dissertation I quantify residential behavior response to interventions designed to reduce electricity demand at different periods of the day. In the first chapter, I examine the effect of information provision coupled with bimonthly billing, monthly billing, and in-home displays, as well as a time-of-use (TOU) pricing scheme to measure consumption over each month of the Irish Consumer Behavior Trial. I find that time-of-use pricing with real time usage information reduces electricity usage up to 8.7 percent during peak times at the start of the trial but the effect decays over the first three months and after three months the in-home display group is indistinguishable from the monthly treatment group. Monthly and bi-monthly billing treatments are not found to be statistically different from another. These findings suggest that increasing billing reports to the monthly level may be more cost effective for electricity generators who wish to decrease expenses and consumption, rather than providing in-home displays. In the following chapter, I examine the response of residential households after exposure to time of use tariffs at different hours of the day. I find that these treatments reduce electricity consumption during peak hours by almost four percent, significantly lowering demand. Within the model, I find evidence of overall conservation in electricity used. In addition, weekday peak reductions appear to carry over to the weekend when peak pricing is not present, suggesting changes in consumer habit. The final chapter of my dissertation imposes a system wide time of use plan to analyze the potential reduction in carbon emissions from load shifting based on the Ireland and Northern Single Electricity Market. I find that CO2 emissions savings are highest during the winter months when load demand is highest and dirtier power plants are scheduled to meet peak demand. TOU pricing allows for shifting in usage from peak usage to off peak usage and this shift in load can be met with cleaner and cheaper generated electricity from imports, high efficiency gas units, and hydro units.

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My thesis consists of three essays that investigate strategic interactions between individuals engaging in risky collective action in uncertain environments. The first essay analyzes a broad class of incomplete information coordination games with a wide range of applications in economics and politics. The second essay draws from the general model developed in the first essay to study decisions by individuals of whether to engage in protest/revolution/coup/strike. The final essay explicitly integrates state response to the analysis. The first essay, Coordination Games with Strategic Delegation of Pivotality, exhaustively analyzes a class of binary action, two-player coordination games in which players receive stochastic payoffs only if both players take a ``stochastic-coordination action''. Players receive conditionally-independent noisy private signals about the normally distributed stochastic payoffs. With this structure, each player can exploit the information contained in the other player's action only when he takes the “pivotalizing action”. This feature has two consequences: (1) When the fear of miscoordination is not too large, in order to utilize the other player's information, each player takes the “pivotalizing action” more often than he would based solely on his private information, and (2) best responses feature both strategic complementarities and strategic substitutes, implying that the game is not supermodular nor a typical global game. This class of games has applications in a wide range of economic and political phenomena, including war and peace, protest/revolution/coup/ strike, interest groups lobbying, international trade, and adoption of a new technology. My second essay, Collective Action with Uncertain Payoffs, studies the decision problem of citizens who must decide whether to submit to the status quo or mount a revolution. If they coordinate, they can overthrow the status quo. Otherwise, the status quo is preserved and participants in a failed revolution are punished. Citizens face two types of uncertainty. (a) non-strategic: they are uncertain about the relative payoffs of the status quo and revolution, (b) strategic: they are uncertain about each other's assessments of the relative payoff. I draw on the existing literature and historical evidence to argue that the uncertainty in the payoffs of status quo and revolution is intrinsic in politics. Several counter-intuitive findings emerge: (1) Better communication between citizens can lower the likelihood of revolution. In fact, when the punishment for failed protest is not too harsh and citizens' private knowledge is accurate, then further communication reduces incentives to revolt. (2) Increasing strategic uncertainty can increase the likelihood of revolution attempts, and even the likelihood of successful revolution. In particular, revolt may be more likely when citizens privately obtain information than when they receive information from a common media source. (3) Two dilemmas arise concerning the intensity and frequency of punishment (repression), and the frequency of protest. Punishment Dilemma 1: harsher punishments may increase the probability that punishment is materialized. That is, as the state increases the punishment for dissent, it might also have to punish more dissidents. It is only when the punishment is sufficiently harsh, that harsher punishment reduces the frequency of its application. Punishment Dilemma 1 leads to Punishment Dilemma 2: the frequencies of repression and protest can be positively or negatively correlated depending on the intensity of repression. My third essay, The Repression Puzzle, investigates the relationship between the intensity of grievances and the likelihood of repression. First, I make the observation that the occurrence of state repression is a puzzle. If repression is to succeed, dissidents should not rebel. If it is to fail, the state should concede in order to save the costs of unsuccessful repression. I then propose an explanation for the “repression puzzle” that hinges on information asymmetries between the state and dissidents about the costs of repression to the state, and hence the likelihood of its application by the state. I present a formal model that combines the insights of grievance-based and political process theories to investigate the consequences of this information asymmetry for the dissidents' contentious actions and for the relationship between the magnitude of grievances (formulated here as the extent of inequality) and the likelihood of repression. The main contribution of the paper is to show that this relationship is non-monotone. That is, as the magnitude of grievances increases, the likelihood of repression might decrease. I investigate the relationship between inequality and the likelihood of repression in all country-years from 1981 to 1999. To mitigate specification problem, I estimate the probability of repression using a generalized additive model with thin-plate splines (GAM-TPS). This technique allows for flexible relationship between inequality, the proxy for the costs of repression and revolutions (income per capita), and the likelihood of repression. The empirical evidence support my prediction that the relationship between the magnitude of grievances and the likelihood of repression is non-monotone.

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Education is one of the main industries in the world, which needs to focus more than other types of industries. As Mandela said, “Education is the most powerful weapon, which you can use to change the world” (www.brainyquote.com). Global economic recession era put serious pressure on private Higher Education Institutions (HEI), which resulted as decrease in the university spending`s budget. Therefore, HEI forced to develop more competitive ways to find new financial resources for rapid technological and organizational changes (Savsar, 2012). Students are the motive of being of Higher Education. The aim of this study is to implement İmportance-Satisfaction Analysis (IPA) matrix to evaluate the student`s satisfaction and assess importance of different attributes in terms of student`s perception. The students that participated in this study enrolled in the present academic year, 2015/2016, in the Economics and Administration Faculty-Qafqaz University. In order to perform study, survey method applied to collect the data and number of received valid questionnaire were 266. Questionnaire used to collect demographic information of students, identify importance given to each attribute and satisfaction degree of each attribute. Descriptive analysis used to identify profile of respondents, also find satisfaction and importance degree for each attributes. To evaluate differences between groups, built association between variables, find relation between variables and answering to the research hypothesis inferential analysis applied. Moreover, IPA matrix was been used to explore the attributes that needs improvement that perceived as attributes that are more important for the students. The result showed that generally students are satisfied with service quality offered by HEI-on sample of the Qafqaz University. In addition, research found that there are no differences in overall satisfaction and importance by department, gender, academic year and grade point average. IPA matrix highlighted the main attributes, which performs well, namely Academic Services and Teaching aspects, and in another hand needs to concentrate in Undergraduate program and External Relations. In addition, research found that loyalty of students is very low and there is a negative correlation between loyalty and satisfaction.

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Understanding how imperfect information affects firms' investment decision helps answer important questions in economics, such as how we may better measure economic uncertainty; how firms' forecasts would affect their decision-making when their beliefs are not backed by economic fundamentals; and how important are the business cycle impacts of changes in firms' productivity uncertainty in an environment of incomplete information. This dissertation provides a synthetic answer to all these questions, both empirically and theoretically. The first chapter, provides empirical evidence to demonstrate that survey-based forecast dispersion identifies a distinctive type of second moment shocks different from the canonical volatility shocks to productivity, i.e. uncertainty shocks. Such forecast disagreement disturbances can affect the distribution of firm-level beliefs regardless of whether or not belief changes are backed by changes in economic fundamentals. At the aggregate level, innovations that increase the dispersion of firms' forecasts lead to persistent declines in aggregate investment and output, which are followed by a slow recovery. On the contrary, the larger dispersion of future firm-specific productivity innovations, the standard way to measure economic uncertainty, delivers the ``wait and see" effect, such that aggregate investment experiences a sharp decline, followed by a quick rebound, and then overshoots. At the firm level, data uncovers that more productive firms increase investments given rises in productivity dispersion for the future, whereas investments drop when firms disagree more about the well-being of their future business conditions. These findings challenge the view that the dispersion of the firms' heterogeneous beliefs captures the concept of economic uncertainty, defined by a model of uncertainty shocks. The second chapter presents a general equilibrium model of heterogeneous firms subject to the real productivity uncertainty shocks and informational disagreement shocks. As firms cannot perfectly disentangle aggregate from idiosyncratic productivity because of imperfect information, information quality thus drives the wedge of difference between the unobserved productivity fundamentals, and the firms' beliefs about how productive they are. Distribution of the firms' beliefs is no longer perfectly aligned with the distribution of firm-level productivity across firms. This model not only explains why, at the macro and micro level, disagreement shocks are different from uncertainty shocks, as documented in Chapter 1, but helps reconcile a key challenge faced by the standard framework to study economic uncertainty: a trade-off between sizable business cycle effects due to changes in uncertainty, and the right amount of pro-cyclicality of firm-level investment rate dispersion, as measured by its correlation with the output cycles.

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Doutoramento em Economia.

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This research develops an econometric framework to analyze time series processes with bounds. The framework is general enough that it can incorporate several different kinds of bounding information that constrain continuous-time stochastic processes between discretely-sampled observations. It applies to situations in which the process is known to remain within an interval between observations, by way of either a known constraint or through the observation of extreme realizations of the process. The main statistical technique employs the theory of maximum likelihood estimation. This approach leads to the development of the asymptotic distribution theory for the estimation of the parameters in bounded diffusion models. The results of this analysis present several implications for empirical research. The advantages are realized in the form of efficiency gains, bias reduction and in the flexibility of model specification. A bias arises in the presence of bounding information that is ignored, while it is mitigated within this framework. An efficiency gain arises, in the sense that the statistical methods make use of conditioning information, as revealed by the bounds. Further, the specification of an econometric model can be uncoupled from the restriction to the bounds, leaving the researcher free to model the process near the bound in a way that avoids bias from misspecification. One byproduct of the improvements in model specification is that the more precise model estimation exposes other sources of misspecification. Some processes reveal themselves to be unlikely candidates for a given diffusion model, once the observations are analyzed in combination with the bounding information. A closer inspection of the theoretical foundation behind diffusion models leads to a more general specification of the model. This approach is used to produce a set of algorithms to make the model computationally feasible and more widely applicable. Finally, the modeling framework is applied to a series of interest rates, which, for several years, have been constrained by the lower bound of zero. The estimates from a series of diffusion models suggest a substantial difference in estimation results between models that ignore bounds and the framework that takes bounding information into consideration.

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This paper argues that in order to systematically comprehend the diversity of information organization frameworks, we must look at how aesthetic concerns and economic concerns manifest in decisions made about designing and deploying work practices, structures, and discourse. In order to do this I construct an analytical rubric borne by a definition of aesthetic and economics pertinent to indexing regimes. I take the position that we need to move into a more descriptive stance on practices of knowledge organization, not only in documentary heritage institutions (libraries, archives, and museums), but also into the cultural and artistic realms. By expanding the scope of inquiry we can interrogate the integrity of my assertion above, namely, that a chief concern in systematically understanding information organization frameworks, lies in understanding how such frameworks wrestle with, and manifest along a spectrum drawn from economic to aesthetic decision-making.

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This dissertation consists of three standalone articles that contribute to the economics literature concerning technology adoption, information diffusion, and network economics in one way or another, using a couple of primary data sources from Ethiopia. The first empirical paper identifies the main behavioral factors affecting the adoption of brand new (radical) and upgraded (incremental) bioenergy innovations in Ethiopia. The results highlight the importance of targeting different instruments to increase the adoption rate of the two types of innovations. The second and the third empirical papers of this thesis, use primary data collected from 3,693 high school students in Ethiopia, and shed light on how we should select informants to effectively and equitably disseminate new information, mainly concerning environmental issues. There are different well-recognized standard centrality measures that are used to select informants. These standard centrality measures, however, are based on the network topology---shaped only by the number of connections---and fail to incorporate the intrinsic motivations of the informants. This thesis introduces an augmented centrality measure (ACM) by modifying the eigenvector centrality measure through weighting the adjacency matrix with the altruism levels of connected nodes. The results from the two papers suggest that targeting informants based on network position and behavioral attributes ensures more effective and equitable (gender perspective) transmission of information in social networks than selecting informants on network centrality measures alone. Notably, when the information is concerned with environmental issues.

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FinTech (financial technology, ‘‘FinTech’’) is a double-edged sword as it brings both benefits and risks. This study appraised FinTech’s technological nature that brings changes in complexity in modern financial markets to identify the information deficits and its undesirable outcomes. Besides, as FinTech is still developing, the information regarding, for instance, whether and how to apply regulation may be insufficient for both regulators and those regulated. More one-size-fits-all regulation might accordingly be adopted, thereby resulting in the adverse selection. Through the lens of both law and economics and law and technology, this study suggested AFR (adaptive financial regulation, ‘‘AFR’’) of FinTech to solve the underlying pacing issue. AFR is dynamic, enabling regulatory adjustments and learning. Exploring and collecting information through experiments and learning from experiments are the core of AFR. FinTech regulatory sandboxes epitomize AFR. This study chose Taiwan as a case study. This study found several barriers to adaptive and effective FinTech regulation. Unduly emphasizing consumer protection and the innovation entry criterion by improperly imposing limits on the entry into sandboxes, ignoring post-sandbox mechanisms, and relying on detailed, specific and prescriptive rules to formulate sandboxes are examples. To solve these barriers, this study proposed several solutions by looking into the experiences in other jurisdictions and analyzing. First, striking a balance between encouraging innovation and ensuring financial stability and consumer protection is indispensable. Second, entry to sandboxes should be facilitated by improving the selection criteria. Third, adhering to realizing regulatory adjustment and learning to adapt regulation to technology, this study argued that systematic post-sandbox mechanisms should be established. Fourth, this study recommended “more principles-based sandboxes”. Principles rather than rules should be the base on which sandboxes or FinTech regulation are established. Having principles could provide more flexibility, being easier to adjust and adapt, and better at avoiding.

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In the first chapter, “Political power and the influence of minorities: theory and evidence from Italy”, I analyze the relationship between minority and majority in politics, and how it can influence policy outcomes. I first present a theoretical model describing the possible consequences of an increase in a minority’s political power and show how it can increase difficulties in reaching a compromise on policy outcomes between parties. Furthermore, I empirically test these implications by exploiting the introduction in 2012 of a gender quota in Italian local elections: the increase in female politicians had heterogeneous effects on the level of funding for daycare, based on its differential effects on the share of women councillors. The second chapter, “Marriage patterns and the gender gap in labor force participation: evidence from Italy”, presents evidence highlighting a new possible determinant of the large gender gap in the Italian labor force: endogamy intensity. I argue that endogamy helps preserve social norms stigmatizing working women and reduces the probability of divorce, which disincentivizes women’s participation in the labor force. Endogamy is proxied by the degree of concentration of its surnames’ distribution, and I provide evidence that a more intense custom of endogamy contributed to enlarging gender participation gaps across Italian municipalities in 2001. The third chapter, “Information and quality of politicians: is transparency helping voters?”, studies how voting choices are affected by giving voters more personal information on candidates. I exploit the introduction of the “Spazzacorrotti” law in Italy in 2019, which imposed candidates at local elections to publish their CVs and criminal records before elections. I find no effects on elected candidates’ age, gender, educational level, or ideology. Moreover, I present anecdotal evidence that candidates with a criminal record received fewer votes on average, but only in the case of local media exposing it.

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This research addresses the use of ex ante contracts to arbitrate tort claims in domestic settings using law and economics research methodologies. Potential economic benefits from using arbitration, particularly between informed and knowledgeable parties and in international business transactions, are not guaranteed in domestic disputes. Arbitration can potentially be used to manipulate the adjudication process. This research has several findings. There is a lack of information available concerning the use of arbitration to adjudicate tort claims. Proxy measurements concerning the demand for third party adjudication and other legal indicators are a poor substitute for the information hidden behind the veil of arbitration. There is the potential for the strategic use of ex ante contracts to arbitrate tort claims by repeat player tortfeasors to domestic tort claims, both individually and in concert with other repeat player firms. These strategic efforts aim to: manipulate enforcement errors for tort claims, avoid procedural rules which have the effect of lowering enforcement errors, enable a unique type of domestic forum arbitrage, shirk from taking due care, capture the economic benefit of using arbitration, manipulate the stock of precedents and production of public goods from courts, collude in these underlying efforts, restrain competition, indirectly fix prices, and other aims which increase the repeat player tortfeasor’s or their industries economic gains related to their underlying contracts and tort disputes. This research also demonstrates how this subject is appropriate for further academic research and why states should be cautious of giving carte blanche to arbitrate all domestic tort claims.

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One of the great challenges of the scientific community on theories of genetic information, genetic communication and genetic coding is to determine a mathematical structure related to DNA sequences. In this paper we propose a model of an intra-cellular transmission system of genetic information similar to a model of a power and bandwidth efficient digital communication system in order to identify a mathematical structure in DNA sequences where such sequences are biologically relevant. The model of a transmission system of genetic information is concerned with the identification, reproduction and mathematical classification of the nucleotide sequence of single stranded DNA by the genetic encoder. Hence, a genetic encoder is devised where labelings and cyclic codes are established. The establishment of the algebraic structure of the corresponding codes alphabets, mappings, labelings, primitive polynomials (p(x)) and code generator polynomials (g(x)) are quite important in characterizing error-correcting codes subclasses of G-linear codes. These latter codes are useful for the identification, reproduction and mathematical classification of DNA sequences. The characterization of this model may contribute to the development of a methodology that can be applied in mutational analysis and polymorphisms, production of new drugs and genetic improvement, among other things, resulting in the reduction of time and laboratory costs.

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To assess the completeness and reliability of the Information System on Live Births (Sinasc) data. A cross-sectional analysis of the reliability and completeness of Sinasc's data was performed using a sample of Live Birth Certificate (LBC) from 2009, related to births from Campinas, Southeast Brazil. For data analysis, hospitals were grouped according to category of service (Unified National Health System, private or both), 600 LBCs were randomly selected and the data were collected in LBC-copies through mothers and newborns' hospital records and by telephone interviews. The completeness of LBCs was evaluated, calculating the percentage of blank fields, and the LBCs agreement comparing the originals with the copies was evaluated by Kappa and intraclass correlation coefficients. The percentage of completeness of LBCs ranged from 99.8%-100%. For the most items, the agreement was excellent. However, the agreement was acceptable for marital status, maternal education and newborn infants' race/color, low for prenatal visits and presence of birth defects, and very low for the number of deceased children. The results showed that the municipality Sinasc is reliable for most of the studied variables. Investments in training of the professionals are suggested in an attempt to improve system capacity to support planning and implementation of health activities for the benefit of maternal and child population.