Bootstrap methods for the empirical study of decision-making and information flows in social systems

Abstract: We characterize the statistical bootstrap for the estimation of information theoretic quantities from data, with particular reference to its use in the study of large-scale social phenomena. Our methods allow one to preserve, approximately, the underlying axiomatic relationships of information theory—in particular, consistency under arbitrary coarse-graining—that motivate use of these quantities in the first place, while providing reliability comparable to the state of the art for Bayesian estimators. We show how information-theoretic quantities allow for rigorous empirical study of the decision-making capacities of rational agents, and the time-asymmetric flows of information in distributed systems. We provide illustrative examples by reference to ongoing collaborative work on the semantic structure of the British Criminal Court system and the conflict dynamics of the contemporary Afghanistan insurgency

Oil prices and stock markets: what drives what in the Gulf Corporation Council countries?

In the empirical literature, only few studies have focused on the relationship between oil prices and stock markets in net oil-importing countries. In net oil-exporting countries this relationship has not been widely researched. This paper implements the panel-data approach of Kónya (2006), which is based on SUR systems and Wald tests with country-specific bootstrap critical values to study the sensitivity of stock markets to oil prices in GCC (Gulf Corporation Council) countries. Using two different (weekly and monthly) datasets covering respectively the periods from 7 June 2005 to 21 October 2008, and from January 1996 to December 2007, we show strong statistical evidence that the causal relationship is consistently bi-directional for Saudi Arabia. Stock market price changes in the other GCC member countries do not Granger cause oil price changes, whereas oil price shocks Granger cause stock price changes. Therefore, investors in GCC stock markets should look at the changes in oil prices, whereas investors in oil markets should look at changes in the Saudi stock market.http://deepblue.lib.umich.edu/bitstream/2027.42/64354/1/wp960.pd

About the relations between Management Accounting Systems, Intellectual Capital and Performance

The present study is focused on the contribution of management accounting systems (MAS) in the development of intellectual capital (IC). Based on empirical evidence that supports the proposition that the value creation process is strongly associated to the level of IC, the study also examines the mediating effect of MAS on performance through their positive direct effect on IC. These relationships were consolidated into a model and empirically tested with data from 281 Portuguese firms using the Structural Equation Modeling (SEM). The findings show that six out of nine hypothesized relationships were supported by data with positive and significant causal links between MAS and the human and structural dimensions of IC. Results confirmed the conceptual validity of the circular model for the interactions among the three IC dimensions. Results also showed a positive and significant direct effect of structural capital on performance. Overall, the results confirmed the validity of the proposed model and contributed to the literature on the role of MAS in supporting the development of the I

Oil prices and stock markets: what drives what in the Gulf Corporation Council countries?

In the empirical literature, only few studies have focused on the relationship between oil prices and stock markets in net oil-importing countries. In net oil-exporting countries this relationship has not been widely researched. This paper implements the panel-data approach of Kónya (2006), which is based on SUR systems and Wald tests with country-specific bootstrap critical values to study the sensitivity of stock markets to oil prices in GCC (Gulf Corporation Council) countries. Using two different (weekly and monthly) datasets covering respectively the periods from 7 June 2005 to 21 October 2008, and from January 1996 to December 2007, we show strong statistical evidence that the causal relationship is consistently bi-directional for Saudi Arabia. Stock market price changes in the other GCC member countries do not Granger cause oil price changes, whereas oil price shocks Granger cause stock price changes. Therefore, investors in GCC stock markets should look at the changes in oil prices, whereas investors in oil markets should look at changes in the Saudi stock market.GCC stock markets, oil prices

Oil Prices and Stock Markets: What Drives what in the Gulf Corporation Council Countries?

In the empirical literature, only few studies have focused on the relationship between oil prices and stock markets in net oil-importing countries. In net oil-exporting countries this relationship has not been widely researched. This paper implements the panel-data approach of Kónya (2006), which is based on SUR systems and Wald tests with country-specific bootstrap critical values to study the sensitivity of stock markets to oil prices in GCC (Gulf Corporation Council) countries. Using two different (weekly and monthly) datasets covering respectively the periods from 7 June 2005 to 21 October 2008, and from January 1996 to December 2007, we show strong statistical evidence that the causal relationship is consistently bi-directional for Saudi Arabia. Stock market price changes in the other GCC member countries do not Granger cause oil price changes, whereas oil price shocks Granger cause stock price changes. Therefore, investors in GCC stock markets should look at the changes in oil prices, whereas investors in oil markets should look at changes in the Saudi stock market.GCC stock markets, oil prices

An investigation into machine learning approaches for forecasting spatio-temporal demand in ride-hailing service

In this paper, we present machine learning approaches for characterizing and forecasting the short-term demand for on-demand ride-hailing services. We propose the spatio-temporal estimation of the demand that is a function of variable effects related to traffic, pricing and weather conditions. With respect to the methodology, a single decision tree, bootstrap-aggregated (bagged) decision trees, random forest, boosted decision trees, and artificial neural network for regression have been adapted and systematically compared using various statistics, e.g. R-square, Root Mean Square Error (RMSE), and slope. To better assess the quality of the models, they have been tested on a real case study using the data of DiDi Chuxing, the main on-demand ride hailing service provider in China. In the current study, 199,584 time-slots describing the spatio-temporal ride-hailing demand has been extracted with an aggregated-time interval of 10 mins. All the methods are trained and validated on the basis of two independent samples from this dataset. The results revealed that boosted decision trees provide the best prediction accuracy (RMSE=16.41), while avoiding the risk of over-fitting, followed by artificial neural network (20.09), random forest (23.50), bagged decision trees (24.29) and single decision tree (33.55).Comment: Currently under review for journal publicatio

The civilizing process in London’s Old Bailey

The jury trial is a critical point where the state and its citizens come together to define the limits of acceptable behavior. Here we present a large-scale quantitative analysis of trial transcripts from the Old Bailey that reveal a major transition in the nature of this defining moment. By coarse-graining the spoken word testimony into synonym sets and dividing the trials based on indictment, we demonstrate the emergence of semantically distinct violent and nonviolent trial genres. We show that although in the late 18th century the semantic content of trials for violent offenses is functionally indistinguishable from that for nonviolent ones, a long-term, secular trend drives the system toward increasingly clear distinctions between violent and nonviolent acts. We separate this process into the shifting patterns that drive it, determine the relative effects of bureaucratic change and broader cultural shifts, and identify the synonym sets most responsible for the eventual genre distinguishability. This work provides a new window onto the cultural and institutional changes that accompany the monopolization of violence by the state, described in qualitative historical analysis as the civilizing process

Trade, transition paths, and sustainable economies

The main criticisms of trade from a sustainability viewpoint are that it accelerates resource depletion and pollution, harms income distribution both locally and internationally, and undermines democratic institutions. After considering the relationship between trade and "sustainability," this paper discusses a number of feedback mechanisms which promote the kind of trade that is more sustainable - for the South as well as the North. The role of technological change, a model of the relationship between production and "sustaining services," data needs and research priorities are also discussed

The Role of Performance Measure Characteristics in the Design of Incentive Systems: An Empirical Analysis

In this paper, I derive three general performance measure characteristics from the literature that are theoretically related to the use of performance measures, i.e., (1) the impact that a manager has on performance (sensitivity), (2) the impact that uncontrollable factors have on performance (controllability), and (3) the degree to which the performance measure is objective and verifiable (measurement accuracy). I empirically examine the effect of information asymmetry and the performance measure characteristics on the use of three types of performance measures. Furthermore, I examine how two types of uncertainty, i.e., task uncertainty and environmental uncertainty, affect information asymmetry and performance measure characteristics. The major finding of this study is that sensitivity is positively related to the use of all three types of performance measures, while measurement accuracy is positively related to two out of these three types of performance measures. Controllability, on the other hand, does not have the proposed positive effect on any of the performance measures examined. These results suggest that sensitivity and measurement accuracy play an important role in designing incentive systems, while controllability seems to play no role.accounting and auditing ;

Estimating the historical and future probabilities of large terrorist events

Quantities with right-skewed distributions are ubiquitous in complex social systems, including political conflict, economics and social networks, and these systems sometimes produce extremely large events. For instance, the 9/11 terrorist events produced nearly 3000 fatalities, nearly six times more than the next largest event. But, was this enormous loss of life statistically unlikely given modern terrorism's historical record? Accurately estimating the probability of such an event is complicated by the large fluctuations in the empirical distribution's upper tail. We present a generic statistical algorithm for making such estimates, which combines semi-parametric models of tail behavior and a nonparametric bootstrap. Applied to a global database of terrorist events, we estimate the worldwide historical probability of observing at least one 9/11-sized or larger event since 1968 to be 11-35%. These results are robust to conditioning on global variations in economic development, domestic versus international events, the type of weapon used and a truncated history that stops at 1998. We then use this procedure to make a data-driven statistical forecast of at least one similar event over the next decade.Comment: Published in at http://dx.doi.org/10.1214/12-AOAS614 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org