958 resultados para business intelligence
Resumo:
This paper is inspired by articles in the last decade or so that have argued for more attention to theory, and to empirical analysis, within the well-known, and long-lasting, contingency framework for explaining the organisational form of the firm. Its contribution is to extend contingency analysis in three ways: (a) by empirically testing it, using explicit econometric modelling (rather than case study evidence) involving estimation by ordered probit analysis; (b) by extending its scope from large firms to SMEs; (c) by extending its applications from Western economic contexts, to an emerging economy context, using field work evidence from China. It calibrates organizational form in a new way, as an ordinal dependent variable, and also utilises new measures of familiar contingency factors from the literature (i.e. Environment, Strategy, Size and Technology) as the independent variables. An ordered probit model of contingency was constructed, and estimated by maximum likelihood, using a cross section of 83 private Chinese firms. The probit was found to be a good fit to the data, and displayed significant coefficients with plausible interpretations for key variables under all the four categories of contingency analysis, namely Environment, Strategy, Size and Technology. Thus we have generalised the contingency model, in terms of specification, interpretation and applications area.
Resumo:
We study a business cycle model in which a benevolent fiscal authority must determine the optimal provision of government services, while lacking credibility, lump-sum taxes, and the ability to bond finance deficits. Households and the fiscal authority have risk sensitive preferences. We find that outcomes are affected importantly by the household's risk sensitivity, but not by the fiscal authority's. Further, while household risk-sensitivity induces a strong precautionary saving motive, which raises capital and lowers the return on assets, its effects on fluctuations and the business cycle are generally small, although more pronounced for negative shocks. Holding the stochastic steady state constant, increases in household risk-sensitivity lower the risk-free rate and raise the return on equity, increasing the equity premium. Finally, although risk-sensitivity has little effect on the provision of government services, it does cause the fiscal authority to lower the income tax rate. An additional contribution of this paper is to present a method for computing Markov-perfect equilibria in models where private agents and the government are risk-sensitive decisionmakers.
Resumo:
This paper analyses optimal income taxes over the business cycle under a balanced-budget restriction, for low, middle and high income households. A model incorporating capital-skill complementarity in production and differential access to capital and labour markets is developed to capture the cyclical characteristics of the US economy, as well as the empirical observations on wage (skill premium) and wealth inequality. We .nd that the tax rate for high income agents is optimally the least volatile and the tax rate for low income agents the least countercyclical. In contrast, the path of optimal taxes for the middle income group is found to be very volatile and counter-cyclical. We further find that the optimal response to output-enhancing capital equipment technology and spending cuts is to increase the progressivity of income taxes. Finally, in response to positive TFP shocks, taxation becomes more progressive after about two years.
Resumo:
Motivated by the highly-unionized public sectors, the high public shares in total employment, and the public sector wage premia observed in Europe, this paper examines the importance of public sector unions for macroeconomic theory. The model generates cyclical behavior in hours and wages that is consistent with data behavior in an economy with highly-unionized public sector, namely Germany during the period 1970-2007. The union model is a signifi cant improvement over a model with exogenous public employment. In addition, endogenously-determined public wage and hours add to the distortionary e ffect of contractionary tax reforms by generating greater tax rate changes, thus producing signi ficantly higher welfare losses.
Resumo:
This paper studies the wasteful e ffect of bureaucracy on the economy by addressing the link between rent-seeking behavior of government bureaucrats and the public sector wage bill, which is taken to represent the rent component. In particular, public o fficials are modeled as individuals competing for a larger share of those public funds. The rent-seeking extraction technology in the government administration is modeled as in Murphy et al. (1991) and incorporated in an otherwise standard Real-Business-Cycle (RBC) framework with public sector. The model is calibrated to German data for the period 1970-2007. The main fi ndings are: (i) Due to the existence of a signi ficant public sector wage premium and the high public sector employment, a substantial amount of working time is spent rent-seeking, which in turn leads to signifi cant losses in terms of output; (ii) The measures for the rent-seeking cost obtained from the model for the major EU countries are highly-correlated to indices of bureaucratic ineffi ciency; (iii) Under the optimal scal policy regime,steady-state rent-seeking is smaller relative to the exogenous policy case, as the government chooses a higher public wage premium, but sets a much lower public employment, thus achieving a decrease in rent-seeking.
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An important disconnect in the news driven view of the business cycle formalized by Beaudry and Portier (2004), is the lack of agreement between different—VAR and DSGE—methodologies over the empirical plausibility of this view. We argue that this disconnect can be largely resolved once we augment a standard DSGE model with a financial channel that provides amplification to news shocks. Both methodologies suggest news shocks to the future growth prospects of the economy to be significant drivers of U.S. business cycles in the post-Greenspan era (1990-2011), explaining as much as 50% of the forecast error variance in hours worked in cyclical frequencies
Resumo:
This paper undertakes a normative investigation of the quantitative properties of optimal tax smoothing in a business cycle model with state contingent debt, capital-skill complementarity, endogenous skill formation and stochastic shocks to public consumption as well as total factor and capital equipment productivity. Our main finding is that an empirically relevant restriction which does not allow the relative supply of skilled labour to adjust in response to aggregate shocks, signi cantly changes the cyclical properties of optimal labour taxes. Under a restricted relative skill supply, the government fi nds it optimal to adjust labour income tax rates so that the average net returns to skilled and unskilled labour hours exhibit the same dynamic behaviour as under fl exible skill supply.
Resumo:
This paper studies unemployed workers’ decisions to change occupations, and their impact on fluctuations in aggregate unemployment and its underlying duration distribution. We develop an analytically and computationally tractable stochastic equilibrium model with heterogenous labor markets. In this model three different types of unemployment arise: search, rest and reallocation unemployment. We document new evidence on unemployed workers’ gross occupational mobility and use it to calibrate the model. We show that rest unemployment is the main driver of unemployment fluctuations over the business cycle and causes cyclical unemployment to be highly volatile. The resulting unemployment duration distribution generated by the model responds realistically to the business cycle, creating substantial longer-term unemployment in downturns. Finally, rest unemployment also makes our model simultaneously consistent with procyclical occupational mobility of the unemployed, countercyclical job separations into unemployment and a negatively-sloped Beveridge curve.
Resumo:
Time-inconsistency is an essential feature of many policy problems (Kydland and Prescott, 1977). This paper presents and compares three methods for computing Markov-perfect optimal policies in stochastic nonlinear business cycle models. The methods considered include value function iteration, generalized Euler-equations, and parameterized shadow prices. In the context of a business cycle model in which a scal authority chooses government spending and income taxation optimally, while lacking the ability to commit, we show that the solutions obtained using value function iteration and generalized Euler equations are somewhat more accurate than that obtained using parameterized shadow prices. Among these three methods, we show that value function iteration can be applied easily, even to environments that include a risk-sensitive scal authority and/or inequality constraints on government spending. We show that the risk-sensitive scal authority lowers government spending and income-taxation, reducing the disincentive households face to accumulate wealth.
Resumo:
Research in business dynamics has been advancing rapidly in the last years but the translation of the new knowledge to industrial policy design is slow. One striking aspect in the policy area is that although research and analysis do not identify the existence of an specific optimal rate of business creation and business exit, governments everywhere have adopted business start-up support programs with the implicit principle that the more the better. The purpose of this article is to contribute to understand the implications of the available research for policy design. Economic analysis has identified firm heterogeneity as being the most salient characteristic of industrial dynamics, and so a better knowledge of the different types of entrepreneur, their behavior and their specific contribution to innovation and growth would enable us to see into the ‘black box’ of business dynamics and improve the design of appropriate public policies. The empirical analysis performed here shows that not all new business have the same impact on relevant economic variables, and that self-employment is of quite a different economic nature to that of firms with employees. It is argued that public programs should not promote indiscriminate entry but rather give priority to able entrants with survival capacities. Survival of entrants is positively related to their size at birth. Innovation and investment improve the likelihood of survival of new manufacturing start-ups. Investment in R&D increases the risk of failure in new firms, although it improves the competitiveness of incumbents.
Resumo:
Until recently, much of the discussion regarding the type of organization theory needed in management studies focused on normative vs. descriptive roles of management science. Some authors however noticed that even a descriptive theory can have a normative impact. Among others, management theories are used by practitioners to make sense of their identity and roles in given contexts, and so guide their attitude, decision process, and behavior. The sensemaking potential of a theory might in this view represent an important element for predicting the adoption of a theory by practitioners. Accordingly, theories are needed which better grasp the increased complexity of today's business environment in order to be more relevant for practitioners. This article proposes a multi-faceted perspective of organizations. This implies leaving a simplistic view of organizations and building a 'cubist' conception. Picasso's cubism paintings are characterized by the use of multiple perspectives within a single drawing. Similarly, I argue here that managers must learn not only to add multiple responsibilities in their work, but to develop an integrated conception of their managerial identity and of their organizations in which the multiple social and economic dimensions are enmeshed. Social entrepreneurship is discussed as illustration of typical multi-faceted business.
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In his timely article, Cherniss offers his vision for the future of "Emotional Intelligence" (EI). However, his goal of clarifying the concept by distinguishing definitions from models and his support for "Emotional and Social Competence" (ESC) models will, in our opinion, not make the field advance. To be upfront, we agree that emotions are important for effective decision-making, leadership, performance and the like; however, at this time, EI and ESC have not yet demonstrated incremental validity over and above IQ and personality tests in meta-analyses (Harms & Credé, 2009; Van Rooy & Viswesvaran, 2004). If there is a future for EI, we see it in the ability model of Mayer, Salovey and associates (e.g, Mayer, Caruso, & Salovey, 2000), which detractors and supporters agree holds the most promise (Antonakis, Ashkanasy, & Dasborough, 2009; Zeidner, Roberts, & Matthews, 2008). With their use of quasi-objective scoring measures, the ability model grounds EI in existing frameworks of intelligence, thus differentiating itself from ESC models and their self-rated trait inventories. In fact, we do not see the value of ESC models: They overlap too much with current personality models to offer anything new for science and practice (Zeidner, et al., 2008). In this commentary we raise three concerns we have with Cherniss's suggestions for ESC models: (1) there are important conceptual problems in both the definition of ESC and the distinction of ESC from EI; (2) Cherniss's interpretation of neuroscience findings as supporting the constructs of EI and ESC is outdated, and (3) his interpretation of the famous marshmallow experiment as indicating the existence of ESCs is flawed. Building on the promise of ability models, we conclude by providing suggestions to improve research in EI.
Resumo:
There is an increasing awareness that the articulation of forensic science and criminal investigation is critical to the resolution of crimes. However, models and methods to support an effective collaboration between these partners are still poorly expressed or even lacking. Three propositions are borrowed from crime intelligence methods in order to bridge this gap: (a) the general intelligence process, (b) the analyses of investigative problems along principal perspectives: entities and their relationships, time and space, quantitative aspects and (c) visualisation methods as a mode of expression of a problem in these dimensions. Indeed, in a collaborative framework, different kinds of visualisations integrating forensic case data can play a central role for supporting decisions. Among them, link-charts are scrutinised for their abilities to structure and ease the analysis of a case by describing how relevant entities are connected. However, designing an informative chart that does not bias the reasoning process is not straightforward. Using visualisation as a catalyser for a collaborative approach integrating forensic data thus calls for better specifications.