Suchergebnisse

This book offers hands-on statistical tools for business professionals by focusing on the practical application of a single-equation regression. The authors discuss commonly applied econometric procedures, which are useful in building regression models for economic forecasting and supporting business decisions. A significant part of the book is devoted to traps and pitfalls in implementing regression analysis in real-world scenarios. The book consists of nine chapters, the final two of which are fully devoted to case studies. Today's business environment is characterised by a huge amount of economic data. Making successful business decisions under such data-abundant conditions requires objective analytical tools, which can help to identify and quantify multiple relationships between dozens of economic variables. Single-equation regression analysis, which is discussed in this book, is one such tool. The book offers a valuable guide and is relevant in various areas of economic and business analysis, including marketing, financial and operational management.

Purpose
The purpose of this paper is to study the reasons and decision-making processes of heterogeneous firms' bribery behavior, and how they will affect an aggregate economy's development and corruption status.


Design/methodology/approach
The authors build a dynamic model to study a firm's joint decision to bribe and invest, and how the decision is determined by its production and infrastructure status. The authors simulate the firm-level decision and development paths, and then build an aggregate economy consisting of heterogeneous firms. The authors then also simulate the development and corruption growth paths of the economy, by calibrating the model according to Chinese manufacturing firms in 2012.


Findings
Following the simulation results, the authors conduct counterfactual policy analyses. By comparing between the simulation results of two different counterfactual scenarios, the authors study how a government could control bribing better – as to decrease the number of bribers, and the average amount of the bribery payments. It is found that directly raising the bribery costs works more efficiently in controlling corruption, compared with reducing the benefits received by the bribers. The finding provides insightful policy implications for the government to clear up its economy.


Originality/value
The paper makes a novel and unique contribution to the literature by filling the current theoretical gap. The authors introduce a dynamic firm-level model to interpret firms' bribery decisions and replicate the aggregate stylized facts. The paper innovatively treats bribery as both discrete and continuous decisions. Given both types of bribery decisions, now the authors can successfully simulate and quantify a firm's intertemporal status and growth path.

Tracing the development of economics since the 19th century up to the present day makes it evident that at its core there is a sequence of rather precise and mathematically sophisticated axiomatic theories. At the same time, there is always a noticeable and persistent gap between economic reality and the economic predictions derived from these theories. The main reason why economic theories have not been successful so far in modeling economic reality is the fact that these theories are formulated in terms of hard sciences characterized by their nature of preciseness. In economics, as in any complex multi-agent humanistic system, motivations, intuition, human knowledge, and human behavior, such as perception, emotions, and norms, play dominant roles. Consequently, real economic and socioeconomic world problems are too complex to be translated into classical mathematical and bivalent logic languages, solved and interpreted in the language of the real world. The traditional modeling methodology (economics deals with models of economic reality) is perhaps not relevant or at least not powerful enough to satisfy the requirements of human reasoning and decision making activities. A new much more effective modeling language is needed to capture economic reality. According to Prof. L. Zadeh, in general, fuzzy-logic-based modeling languages have a higher power of cointension than their bivalent logic-based counterparts and present the potential for playing an essential role in modeling economic, social, and political systems. The sheer complexity of causation in the economic arena mandates a fuzzy approach. We argue that many economic dynamical systems naturally become fuzzy due to the uncertain initial conditions and parameters. In this study we consider an economic system as a human centric and imperfect information-based realistic multi-agent system with fuzzy-logic-based representation of the economic agents' behavior and with imprecise constraints. We use fuzzy "if-then" language and fuzzy differential equations for modeling the economic agents. This paper looks beyond the standard assumptions of economics that all people are similarly rational and self-interested. To be able to incorporate motivation input variables of economic agents into their models, we created behavioral model of agents by using the fuzzy and Bayes-Shortliffe approaches. Nowadays, adding norms and motivations to utility function has become an issue for economists and business people. They also recognized that something is missing in standard utility function and even in standard economic theory. Everything is not as simple as just profit or utility maximization under budget constraint. They recognized that during all these years they have been ignoring the most important thing: the norms and motivations that actually directed the human nature of the decision makers. It is obvious that these norms and motivations cannot be captured by statistical analysis, there are deeper and more subtle uncertain relationships between well-being and its determinants. We suggest the fuzzy graph-based approach to utility function construction. The proposed approach is consistent with the behavioral and uncertainty paradigms of the decision makers. Here we put the emphasis on mathematical background rather than real case analysis. The suggested fuzzy approaches to economic problem-solving are applied to fuzzy decision making in an oligopolistic economy.

In portfolio decision analysis, features comprise the objectives, alternatives, physics, and information that define a decision context. By modeling features, decision analysts forecast the expected utilities of the alternatives. A model is complete if it contains all the features. A model is well-calibrated if it correctly predicts the probability distributions of each alternative's utility, whereas ill-calibrated models, like those that suffer the optimizer's curse, do not. Friction identifies qualities of a situation that prevent decision analysts from creating complete, well-calibrated models. When friction is significant, can maximizing expected utility be a suboptimal decision rule? Is satisfying decision theory's axioms a necessary or sufficient condition for good decision making? Can rules that violate the axioms outperform rules that satisfy them? A simulation study of how unbiased, imprecise forecasts of payoffs affect project selection finds that, for the example tested, the answers are yes, no, and yes, which suggests that further studies of friction may be worthwhile. Discussions of friction bookend the study, starting the paper by defining friction and concluding by presenting three frameworks, each one from a different field of study, that provide mathematical tools for studying friction.

"With its emphasis on practical and conceptual aspects, rather than mathematics or formulas, this accessible book has established itself as the go-to resource on confirmatory factor analysis (CFA). Detailed, worked-through examples drawn from psychology, management, and sociology studies illustrate the procedures, pitfalls, and extensions of CFA methodology. The text shows how to formulate, program, and interpret CFA models using popular latent variable software packages (LISREL, Mplus, EQS, SAS/CALIS); understand the similarities and differences between CFA and exploratory factor analysis (EFA); and report results from a CFA study. It is filled with useful advice and tables that outline the procedures. The companion website offers data and program syntax files for most of the research examples, as well as links to CFA-related resources. New to This Edition *Updated throughout to incorporate important developments in latent variable modeling. *Chapter on Bayesian CFA and multilevel measurement models. *Addresses new topics (with examples): exploratory structural equation modeling, bifactor analysis, measurement invariance evaluation with categorical indicators, and a new method for scaling latent variables. *Utilizes the latest versions of major latent variable software packages"--

First published in 1999, Dynamic Issues in Commercial Policy Analysis focuses on the explicit specification of dynamic mechanisms in the formal analytics of trade models. A wide range of modelling approaches is employed to investigate an even wider range of policy issues, with an overall objective of further extension of the basic conceptual framework of applied commercial policy analysis in the direction of dynamic issues and applications. Professors Baldwin and Francois and their contributors emphasise methods for the analysis of interactions between commercial policy and leading policy issues, including investment performance, economic growth and innovation, the location of industry, migration, and the environment

Correlational or second-order linkage analyses (Schulz, 2008) correlate content data points and survey data at the aggregate level. They are generally used to infer the impact of public opinion climate, the media context or media use on individual attitudes, cognitions and behaviors. Correlational linkage analyses make use of data collected at different points in time to be able to describe patterns of change and stability over time and to compensate for the reduced number of observations resulting from aggregating individual-level data. They often employ manual and automated content analysis, descriptive and inferential statistical analyses, and time series analysis. Field of application/theoretical foundation: Linkage analyses have extensively been used in the fields of political communication (Soroka, 2002), EU studies (Brosius et al., 2019a), and more recently, social media and social movements. Studies that employed second-order linkage analyses are related to theories of agenda setting (McCombs & Shaw, 1972), framing (Vliegenthart et al., 2008), or media bias and tone (Brosius et al., 2019b) (see chapter Content Analysis in Mixed Method approaches for a detailed account of applications and advantages of using linkage analyses). Example studies: In this data entry we describe two studies that regress survey data on media content data with additional weighs to better model news media effects. The first study (Boomgaarden & Vliegenthart, 2007) weigh media coverage of a particular topic (immigration) by issue prominence and circulation of the newspapers considered in the study. The second one (Vliegenthart et al., 2008) further introduces a publication recency moderator to account for how close in time a given news story was published from when survey data was collected and individuals may have been exposed to such piece of information. References Boomgaarden, H. G., & Vliegenthart, R. (2007). Explaining the rise of anti-immigrant parties: The role of news media content. Electoral Studies, 26(2), ...

Front Cover; Decision Support Systems: Issues and Challenges; Copyright Page; FOREWORD; Table of Contents; PART 1: FRAMEWORK PAPERS; PART 2: RESOURCE DISCIPLINE PAPERS; PART 3: APPLICATION EXPERIENCE PAPERS; PART 4: PARALLEL SESSIONS: ISSUES FOR THE FUTURE IN DSS; CHAPTER 1. INTRODUCTION; CHAPTER 2. A FRAMEWORK FOR RESEARCH ON DECISION SUPPORT SYSTEMS; INTRODUCTION; DEFINITIONS; THREE VIEWS OF DSS; THE MANAGER'S VIEW: PERFORMANCE OBJECTIVES; THE DESIGNER'S OR BUILDER'S VIEW; THE TOOLSMITH'S VIEW; RESEARCH; SUMMARY; REFERENCES; CHAPTER 3. DECISION SUPPORT SYSTEMS: A RESEARCH PERSPECTIVE*