Search results for "causa."
showing 10 items of 647 documents
What Do Chinese Entrepreneurs Think about Entrepreneurship: A Case Study of Popular Essays on Zhisland
2020
Entrepreneurship is becoming increasingly essential in this current era of the knowledge economy. It contributes to the innovation of products and services as well as improved processes. In the long-run, it can also improve the sustainability of the economy by depicting better efficiency and social goals. To stimulate entrepreneurship, it is essential to investigate the thinking behind entrepreneurship or what entrepreneurs think about entrepreneurship. Such investigations should encompass the mental images of entrepreneurs. In this regard, content analysis, based on the popular Zhisland essays, may be applied to elicit opinions from Chinese entrepreneurs about activities, critical factors …
Environmental Risk Score of subclinical Psychopathology risk in children
2020
Current knowledge on environmental causation for psychiatric disorders suggests a complex picture with a multitude of social, physical and chemical exposures occurring at different stages of life. ...
Stock Earnings and Bond Yields in the US 1871 - 2016: The Story of a Changing Relationship
2018
Using historical data that spans almost 150 years, we examine whether there is a long-run equilibrium relationship between the stock's earnings and bond yields. The novelty of our econometric methodology consists in using a vector error correction model where we allow multiple structural breaks in the equilibrium relationship. The results of our analysis suggest the existence of equilibrium relationship over 1871-1929 and 1958-2017. On the two historical segments, our analysis finds that the stock's earnings yield followed the bond yield in both the short- and long-run, but not the other way around. Perhaps the most important and surprising finding of our empirical study is that, after the …
Demography and Economic Growth in Spain: A Time Series Analysis
2003
In this paper, advanced time series econometric tools are employed to test the existence of relationships among demographic and macroeconomic variables in Spain along the 1960-2000 period. Annual data for the total fertility rate, infant mortality rate, per capita gross domestic product and wages are used in the empirical analysis. We first examine the bivariate Granger causality to look for short run relations. Then, a multivariate cointegration analysis is carry out, showing that two long run relationships among the variables exist with statistically significant coefficients. From these cointegration vectors, the vector error correction model is estimated to test the endogenous or exogeno…
A cross-country study of skills and unemployment flows
2021
AbstractUsing an international survey that directly assesses the cognitive skills of the adult population, I study the relation between skills and unemployment flows across 37 countries. Depending on the specifically assessed domain, I document that skills have an unconditional correlation with the log-risk-ratio of exiting to entering unemployment of 0.65–0.68 across the advanced and skill-abundant countries in the sample. The relation is remarkably robust and it is unlikely to be due to reverse causality. I do not find evidence that this positive relation extends to the seven relatively less advanced and less skill-abundant countries in the sample: Peru, Ecuador, Indonesia, Mexico, Chile,…
Effectiveness of Private and Public High Schools: Evidence from Finland
2019
Abstract A number of papers have compared the effectiveness of private and public schools in different institutional settings. However, most of these studies are observational and do not utilize experimental or quasi-experimental design to evaluate the value-added or the effectiveness of private schools in comparison to public schools. This study focuses on private and public high schools in Helsinki, the capital city of Finland. We use two different methods to compare private and public schools, value-added estimation and regression discontinuity design (RDD). Although based on somewhat different assumptions, both methods allow us to evaluate the causal effect of private schools on the exi…
Comparison of Causality Network Estimation in the Sensor and Source Space: Simulation and Application on EEG
2021
The usage of methods for the estimation of the true underlying connectivity among the observed variables of a system is increasing, especially in the domain of neuroscience. Granger causality and similar concepts are employed for the estimation of the brain network from electroencephalogram (EEG) data. Also source localization techniques, such as the standardized low resolution electromagnetic tomography (sLORETA), are widely used for obtaining more reliable data in the source space. In this work, connectivity structures are estimated in the sensor and in the source space making use of the sLORETA transformation for simulated and for EEG data with episodes of spontaneous epileptiform discha…
On the interpretability and computational reliability of frequency-domain Granger causality
2017
This Correspondence article is a comment which directly relates to the paper “A study of problems encountered in Granger causality analysis from a neuroscience perspective” (Stokes and Purdon, 2017). We agree that interpretation issues of Granger causality (GC) in neuroscience exist, partially due to the historically unfortunate use of the name “causality”, as described in previous literature. On the other hand, we think that Stokes and Purdon use a formulation of GC which is outdated (albeit still used) and do not fully account for the potential of the different frequency-domain versions of GC; in doing so, their paper dismisses GC measures based on a suboptimal use of them. Furthermore, s…
Simplifying Probabilistic Expressions in Causal Inference
2018
Obtaining a non-parametric expression for an interventional distribution is one of the most fundamental tasks in causal inference. Such an expression can be obtained for an identifiable causal effect by an algorithm or by manual application of do-calculus. Often we are left with a complicated expression which can lead to biased or inefficient estimates when missing data or measurement errors are involved. We present an automatic simplification algorithm that seeks to eliminate symbolically unnecessary variables from these expressions by taking advantage of the structure of the underlying graphical model. Our method is applicable to all causal effect formulas and is readily available in the …
A perspective on Gaussian processes for Earth observation
2019
Earth observation (EO) by airborne and satellite remote sensing and in-situ observations play a fundamental role in monitoring our planet. In the last decade, machine learning and Gaussian processes (GPs) in particular has attained outstanding results in the estimation of bio-geo-physical variables from the acquired images at local and global scales in a time-resolved manner. GPs provide not only accurate estimates but also principled uncertainty estimates for the predictions, can easily accommodate multimodal data coming from different sensors and from multitemporal acquisitions, allow the introduction of physical knowledge, and a formal treatment of uncertainty quantification and error pr…