Multiple Time Series Analysis for organizational research

While multiple time-series analysis (MTSA) is a well-established method in economics, marketing, and finance, few studies have applied MTSA in organizational research. With the growing availability of data sources that contain detailed time-series data and the increasing importance of longitudinal designs, we argue that MTSA blends well with organizational research. We exemplify the possible applications of MTSA to the topics of social media, innovation, ambidexterity, and top management teams. We illustrate the state-of-the-art MTSA technique – Vector Autoregressive (VAR) model – by explaining the key methodological steps needed to estimate and interpret the results and providing a software tutorial in R and STATA. In line with the rising popularity of social media data, we employ a dataset that combines public social media data from Facebook with corporate reputation data from a private data source. We conclude with a discussion on the applicability, limitations, and extensions of MTSA for academics and practitioners.     

Index to Articles,by Author,Volume 2 (1984)

This article investigates the statistical properties of the U.S. sacrifice ratio—the cumulative output loss arising from a permanent reduction in inflation. We derive estimates of the sacrifice ratio from three structural vector autoregression models and then conduct a series of simulation exercises to analyze their sampling distribution. We obtain point estimates of the sacrifice ratio that are consistent with results reported in earlier studies. However, the estimates are very imprecise, which we suggest reflects the poor quality of instruments used in estimation. We conclude that the estimates provide a very unreliable guide for assessing the output cost of disinflation policy.     

城镇化发展与财政政策相关关系的实证分析

近些年来的实践经验表明,我国城镇化水平的逐步上升与财政政策的支持有着密切的关系,因此建立合理的城镇化财政政策支持体系是我国面临的重大现实课题。本文突破了规范性研究的范畴,将财政政策对城镇化发展的支持进行量化,通过建立在向量自回归模型的基础上,运用脉冲响应函数和预测方差分解来研究财政政策和城镇化发展之间的动态相关性以及三者之间的交互响应情况和响应路径。     

Price controls, trade protectionism and political business cycles in the U.S. steel industry

The U.S. steel industry is subject to a microeconomic political business cycle resulting from U.S. Presidents designing protectionist policies on behalf of the steel industry; experiencing complaints from consumers and foreign producers as a result of the policy; modifying the policy which results in complaints from the steel industry; and finally, maneuvering policy back in favor of the industry to achieve re-election. Using a cointegrating vector error correction framework, this paper tests the hypothesized political business cycle for its effect on steel prices. We find that trade protectionism does not seem to have succeeded in its primary objective of supporting prices. By expending so much political capital on ineffective trade protection, the steel industry may have lost the opportunity to focus on more substantive issues that might have restrained factor cost and enhanced its competitive ability. The devolution of the steel industry, ironically, may have resulted from it's persistent pleas for protection. Political business cycles in the steel industry, with all its attendant negative consequences, would not occur if the steel industry did not continually lobby for protection.     

A note on the construction of optimal linear codes

Let us denote by (n,k,d)-code, a binary linear code with code length nk information symbols and the minimum distance d. It is well known that the problem of obtaining a binary linear code whose code length n is minimum among (n,k,d)-codes for given integers k and d, is equivalent to solve a linear programming whose solutions correspond to a minimum redundancy error-correcting code. In this paper it will be shown that for some given integers d, there exists no solution of the linear programming except a solution which is obtained using a flat in a finite projective geometry.     

Estimating Social Influences from Social Networking Sites—Articulated Friendships versus Communication Interactions

Despite the ubiquity of social networking sites, the online social networking industry is in search of effective marketing strategies to better profit from their established user base. Social media marketing strategies build on the premise that the social network of online users can be predicted and social influences among online users can be estimated. However, the existence of various heterogeneous social interactions on social networking sites presents a challenge for social network prediction and social influence estimation. In this article we draw upon the literatures on self‐presentation on social networking sites and signaling in online social networking to categorize six heterogeneous online social interactions on social networking sites into two types—articulated friendships and communication interactions. This article provides empirical evidence for the differences between articulated friendships and communication interactions and the corresponding articulated and communication networks. In order to compare the impacts of the social influences based on these two networks, we utilize support vector machines to build a classifier to predict virtual community membership and we further estimate the marginal effects of these social influences using a two‐stage probit least squares method. We find significant explanatory power of social influences in predicting virtual community membership. Although the communication network is much sparser than the articulated network, social influences based on the communication network achieve similar performance as the articulated network. These findings provide important implications for social media marketing as well as the management of virtual communities.     

Forecasting and conditional projection using realistic prior distributions

This paper develops a forecasting procedure based on a Bayesian method for estimating vector autoregressions. The procedure is applied t o 10 macroeconomic variables and is shown to improve out-of-sample forecasts relative to univariate equations. Although cross-variable responses are damped by the prior, considerable interaction among the variables is shown to be captured by the estimates

We provide unconditional forecasts as of 1982:12 and 1983:3. We also describe how a model such as this can be used to make conditional projections and to analyze policy alternatives. As an example, we analyze a Congressional Budget Office forecast made in 1982: 12

Although no automatic causal interpretations arise from models like ours, they provide a detailed characterization of the dynamic statistical interdependence of a set of economic variables, information that may help in evaluating causal hypotheses without containing any such hypotheses.     

点与平面的相关位置的拓广

本文利用离差具有判别点与平面的位置关系的特性,用以判别多个平面的位置关系。     

利用向量证明德萨格(Desargues)定理

本文利用向量证明德萨格(Desargues)定理,这使得该定理的证明更为简单、明了、直观。