Extending contingency: the impact of strategy, technology, size and business environment on the organisational form of small Chinese firms

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.

On making causal claims: A review and recommendations

Social scientists often estimate models from correlational data, where the independent variable has not been exogenously manipulated; they also make implicit or explicit causal claims based on these models. When can these claims be made? We answer this question by first discussing design and estimation conditions under which model estimates can be interpreted, using the randomized experiment as the gold standard. We show how endogeneity--which includes omitted variables, omitted selection, simultaneity, common methods bias, and measurement error--renders estimates causally uninterpretable. Second, we present methods that allow researchers to test causal claims in situations where randomization is not possible or when causal interpretation is confounded, including fixed-effects panel, sample selection, instrumental variable, regression discontinuity, and difference-in-differences models. Third, we take stock of the methodological rigor with which causal claims are being made in a social sciences discipline by reviewing a representative sample of 110 articles on leadership published in the previous 10 years in top-tier journals. Our key finding is that researchers fail to address at least 66 % and up to 90 % of design and estimation conditions that make causal claims invalid. We conclude by offering 10 suggestions on how to improve non-experimental research.

Ethnic and religious polarization and social conflict

In this paper we examine the link between ethnic and religious polarization and conflict using interpersonal distances for ethnic and religious attitudes obtained from the World Values Survey. We use the Duclos et al (2004) polarization index. We measure conflict by means on an index of social unrest, as well as by the standard conflict onset or incidence based on a threshold number of deaths. Our results show that taking distances into account significantly improves the quality of the fit. Our measure of polarization outperforms the measure used by Montalvo and Reynal-Querol (2005) and the fractionalization index. We also obtain that both ethnic and religious polarization are significant in explaining conflict. The results improve when we use an indicator of social unrest as the dependent variable.

Disagreements among cohabiting and married couples in 22 European countries

Background: Cross-national research suggests that married people have higher levels of well-being than cohabiting people. However, relationship quality has both positive and negative dimensions. Researchers have paid little attention to disagreements within cohabiting and married couples. Objective: This study aims to improve our understanding of the meaning of cohabitation by examining disagreements within marital and cohabiting relationships. We examine variations in couples' disagreements about housework, paid work and money by country and gender. Methods: The data come from the 2004 European Social Survey. We selected respondents living in a heterosexual couple relationship and aged between 18 and 45. In total, the study makes use of data from 22 European countries and 9,657 people. Given that our dependent variable was dichotomous, we estimated multilevel logit models, with (1) disagree and (0) never disagree. Results: We find that cohabitors had more disagreements about housework, the same disagreements about money, but fewer disagreements about paid work than did married people. These findings could not be explained by socio-economic or demographic measures, nor did we find gender or cross-country differences in the association between union status and conflict. Conclusions: Cohabiting couples have more disagreements about housework but fewer disagreements about paid work than married people. There are no gender or cross-country differences in these associations. The results provide further evidence that the meaning of cohabitation differs from that of marriage, and that this difference remains consistent across nations.

Ageing Prisoners' Disease Burden: Is Being Old a Better Predictor than Time Served in Prison?

Background: The number of older prisoners entering and ageing in prison has increased in the last few decades. Ageing prisoners pose unique challenges to the prison administration as they have differentiated social, custodial and healthcare needs than prisoners who are younger and relatively healthier. Objective: The goal of this study was to explore and compare the somatic disease burden of old and young prisoners, and to examine whether it can be explained by age group and/or time served in prison. Methods: Access to prisoner medical records was granted to extract disease and demographic information of older (>50 years) and younger (≤49 years) prisoners in different Swiss prisons. Predictor variables included the age group and the time spent in prison. The dependent variable was the total number of somatic diseases as reported in the medical records. Results were analysed using descriptive statistics and a negative binomial model. Results: Data of 380 male prisoners from 13 different prisons in Switzerland reveal that the mean ages of older and younger prisoners were 58.78 and 34.26 years, respectively. On average, older prisoners have lived in prison for 5.17 years and younger prisoners for 2.49 years. The average total number of somatic diseases reported by older prisoners was 2.26 times higher than that of prisoners below 50 years of age (95% CI 1.77-2.87, p < 0.001). Conclusion: This study is the first of its kind to capture national disease data of prisoners with a goal of comparing the disease burden of older and younger prisoners. Study findings indicate that older inmates suffer from more somatic diseases and that the number of diseases increases with age group. Results clearly illustrate the poorer health conditions of those who are older, their higher healthcare burden, and raises questions related to the provision of healthcare for inmates growing old in prison. © 2014 S. Karger AG, Basel.

Influencia de las características individuales y de las condiciones laborales en la gravedad de las lesiones por accidente de trabajo registradas en Andalucía en 2003

Background. The study of the severity of occupational injuries is very important for the establishment of prevention plans. The aim of this paper is to analyze the distribution of occupational injuries by a) individual factors b) work place characteristics and c) working conditions and to analyze the severity of occupational injuries by this characteristics in men and women in Andalusia. Methods. Injury data came from the accident registry of the Ministry of Labor and Social Issues in 2003. Dependent variable: the severity of the injury: slight, serious, very serious and fatal; the independent variables: the characteristics of the worker, company data, and the accident itself. Bivariate and multivariate analysis were done to estimate the probability of serious, very serious and fatal injury, related to other variables, through odds ratio (OR), and using a 95% confidence interval (CI 95%). Results. The 82,4% of the records were men and 17,6% were women, of whom the 78,1% are unskilled manual workers, compared to 44,9% of men. The men belonging to class I have a higher probability of more severe lesions (OR = 1,67, 95% CI = 1,17 – 2,38). Conclusions. The severity of the injury is associated with sex, age and type of injury. In men it is also related with the professional situation, the place where the accident happened, an unusual job, the size and the characteristics of the company and the social class, and in women with the sector

Freedom of choice of specialist physicians is important to Swiss resident: a cross-sectional study.

QUESTION UNDER STUDY: To assess how important the possibility to choose specialist physicians is for Swiss residents and to determine which variables are associated with this opinion. METHODS: This cross-sectional study used data from the 2007 Swiss population-based health survey and included 13,642 non-institutionalised adults who responded to the telephone and paper questionnaires. The dependent variable included answers to the question "How important is it for you to be able to choose the specialist you would like to visit?" Independent variables included socio-demographics, health and past year healthcare use measures. Crude and adjusted logistic regressions for the importance of being able to choose specialist physicians were performed, accounting for the survey design. RESULTS: 45% of participants found it very important to be able to choose the specialist physician they wanted to visit. The answers "rather important", "rather not important" and "not important" were reported by 28%, 20% and 7% of respondents. Women, individuals in middle/high executive position, those with an ordinary insurance scheme, those reporting ≥2 chronic conditions or poorer subjective health, or those who had had ≥2 outpatient visits in the preceding year were more likely to find this choice very important. CONCLUSIONS: In 2007, almost half of all Swiss residents found it very important to be able to choose his/her specialist physician. The further development of physician networks or other chronic disease management initiatives in Switzerland, towards integrated care, need to pay attention to the freedom of choice of specialist physicians that Swiss residents value. Future surveys should provide information on access and consultations with specialist physicians.

Protocolo de investigación del atlas de mortalidad de las capitales de provincia de Andalucía y Cataluña (Proyecto AMCAC).

The aim of this work is to make known the multicentric project AMCAC, whose objective is to describe the geographical distribution of mortality from all causes in census groups of the provincial capitals of Andalusia and Catalonia during 1992-2002 and 1994-2000 respectively, and to study the relationship between the sociodemographic characteristics of the census groups and mortality. This is an ecological study in which the analytical unit is the census group. The data correspond to 298,731 individuals (152,913 men and 145,818 women) who died during the study periods in the towns of Almeria, Barcelona, Cadiz, Cordoba, Girona, Granada, Huelva, Jaen, Lleida, Malaga, Seville and Tarragona during the study periods. The dependent variable is the number of deaths observed per census group. The independent variables are the percentage of unemployment, illiteracy and manual workers. Estimation of the moderated relative risk and the study of the associations among the sociodemographic characteristics of the census groups and the mortality will be done for each town and each sex using the Besag-York-Mollie model. Dissemination of the results will help to improve and broaden knowledge about the population's health, and will provide an important starting point to establish the influence of contextual variables on the health of urban populations.

PyRate: a new program to estimate speciation and extinction rates from incomplete fossil data

Despite the advancement of phylogenetic methods to estimate speciation and extinction rates, their power can be limited under variable rates, in particular for clades with high extinction rates and small number of extant species. Fossil data can provide a powerful alternative source of information to investigate diversification processes. Here, we present PyRate, a computer program to estimate speciation and extinction rates and their temporal dynamics from fossil occurrence data. The rates are inferred in a Bayesian framework and are comparable to those estimated from phylogenetic trees. We describe how PyRate can be used to explore different models of diversification. In addition to the diversification rates, it provides estimates of the parameters of the preservation process (fossilization and sampling) and the times of speciation and extinction of each species in the data set. Moreover, we develop a new birth-death model to correlate the variation of speciation/extinction rates with changes of a continuous trait. Finally, we demonstrate the use of Bayes factors for model selection and show how the posterior estimates of a PyRate analysis can be used to generate calibration densities for Bayesian molecular clock analysis. PyRate is an open-source command-line Python program available at http://sourceforge.net/projects/pyrate/.

Hacia un modelo de análisis de políticas públicas operativ : Un enfoque basado en los actores, sus recursos y las instituciones

Towards an operative analysis of public policies: An approach focused on actors, resources and institutions. This article develops an analytical model which is centred on the individual and collective behaviour of actors involved during different stages of public policy. We postulate that the content and institutional characteristics of public action (dependent variable) are the result of interactions between political-administrative authorities, on the one hand, and, on the other, social groups which cause or suffer the negative effects of a collective problem which public action attempts to resolve (independent variables). The 'game' of the actors depends not only on their particular interests, but also on their resources (money, time, consensus, organization, rights, infrastructure, information, personnel, strength, political support) which they are able to exploit to defend their positions, as well as on the institutional rules which frame these policy games.

Eliciting consumers preferences using stated preference discrete choice models: Contingent ranking versus choice experiment

The aim of this paper is twofold: firstly, to carry out a theoreticalreview of the most recent stated preference techniques used foreliciting consumers preferences and, secondly, to compare the empiricalresults of two dierent stated preference discrete choice approaches.They dier in the measurement scale for the dependent variable and,therefore, in the estimation method, despite both using a multinomiallogit. One of the approaches uses a complete ranking of full-profiles(contingent ranking), that is, individuals must rank a set ofalternatives from the most to the least preferred, and the other usesa first-choice rule in which individuals must select the most preferredoption from a choice set (choice experiment). From the results werealize how important the measurement scale for the dependent variablebecomes and, to what extent, procedure invariance is satisfied.

Role of high normal gamma-glutamyltransferase level in identifying heavy alcohol use in young men.

The objective of the current study was to determine the predictive value of high normal gamma-glutamyltransferase (GGT) level as an indication of heavy drinking in young men. In a sample of 577 men attending a one-day army recruitment process mandatory for all Swiss men at age 19 years, GGT level was evaluated as the dependent variable for each of eight dichotomous classifications of individuals on the basis of meeting cut-off criteria for five indexes of alcohol use, two indexes of alcohol-related problems, and one index of body mass. The sensitivity, specificity, and predictive values of GGT level in identifying subjects as either heavy drinkers or being overweight were determined. Compared with findings for their counterparts, GGT level was higher in subjects reporting consumption of more than 14 drinks per week (20.5 +/- 7.81 vs. 18.9 +/- 7.60, P <.05), in those reporting being drunk at least once during the past 30 days (20.3 +/- 7.80 vs. 18.3 +/- 7.43, P <.001), and in individuals with body mass indexes >or=25 kg/m(2) (25.8 +/- 10.84 vs. 18.3 +/- 6.59, P <.001). At a GGT level cut-off of 20 U/l, the sensitivity, specificity, and positive and negative predictive values of either being a heavy drinker or overweight were 48.2%, 70.2%, 67.7%, and 51.2%, respectively. Exclusion of subjects with body mass indexes of >or=25 kg/m(2) revealed similar results. High normal GGT level in young men is indicative of heavy alcohol use or being overweight; when present, subjects should be screened further for potential concomitant drinking problems.

On making causal claims: A review and recommendations

Social scientists often estimate models from correlational data, where the independent variable has not been exogenously manipulated; they also make implicit or explicit causal claims based on these models. When can these claims be made? We answer this question by first discussing design and estimation conditions under which model estimates can be interpreted, using the randomized experiment as the gold standard. We show how endogeneity--which includes omitted variables, omitted selection, simultaneity, common methods bias, and measurement error--renders estimates causally uninterpretable. Second, we present methods that allow researchers to test causal claims in situations where randomization is not possible or when causal interpretation is confounded, including fixed-effects panel, sample selection, instrumental variable, regression discontinuity, and difference-in-differences models. Third, we take stock of the methodological rigor with which causal claims are being made in a social sciences discipline by reviewing a representative sample of 110 articles on leadership published in the previous 10 years in top-tier journals. Our key finding is that researchers fail to address at least 66 % and up to 90 % of design and estimation conditions that make causal claims invalid. We conclude by offering 10 suggestions on how to improve non-experimental research.

Main-Channel Slopes of Selected Streams in Iowa for Estimation of Flood-Frequency Discharges, November 2004

This report describes a statewide study conducted to develop main-channel slope (MCS) curves for 138 selected streams in Iowa with drainage areas greater than 100 square miles. MCS values determined from the curves can be used in regression equations for estimating flood frequency discharges. Multi-variable regression equations previously developed for two of the three hydrologic regions defined for Iowa require the measurement of MCS. Main-channel slope is a difficult measurement to obtain for large streams using 1:24,000-scale topographic maps. The curves developed in this report provide a simplified method for determining MCS values for sites located along large streams in Iowa within hydrologic Regions 2 and 3. The curves were developed using MCS values quantified for 2,058 selected sites along 138 selected streams in Iowa. A geographic information system (GIS) technique and 1:24,000-scale topographic data were used to quantify MCS values for the stream sites. The sites were selected at about 5-mile intervals along the streams. River miles were quantified for each stream site using a GIS program. Data points for river-mile and MCS values were plotted and a best-fit curve was developed for each stream. An adjustment was applied to all 138 curves to compensate for differences in MCS values between manual measurements and GIS quantification. The multi-variable equations for Regions 2 and 3 were developed using manual measurements of MCS. A comparison of manual measurements and GIS quantification of MCS indicates that manual measurements typically produce greater values of MCS compared to GIS quantification. Median differences between manual measurements and GIS quantification of MCS are 14.8 and 17.7 percent for Regions 2 and 3, respectively. Comparisons of percentage differences between flood-frequency discharges calculated using MCS values of manual measurements and GIS quantification indicate that use of GIS values of MCS for Region 3 substantially underestimate flood discharges. Mean and median percentage differences for 2- to 500-year recurrence-interval flood discharges ranged from 5.0 to 5.3 and 4.3 to 4.5 percent, respectively, for Region 2 and ranged from 18.3 to 27.1 and 12.3 to 17.3 percent for Region 3. The MCS curves developed from GIS quantification were adjusted by 14.8 percent for streams located in Region 2 and by 17.7 percent for streams located in Region 3. Comparisons of percentage differences between flood discharges calculated using MCS values of manual measurements and adjusted-GIS quantification for Regions 2 and 3 indicate that the flood-discharge estimates are comparable. For Region 2, mean percentage differences for 2- to 500-year recurrence-interval flood discharges ranged between 0.6 and 0.8 percent and median differences were 0.0 percent. For Region 3, mean and median differences ranged between 5.4 to 8.4 and 0.0 to 0.3 percent, respectively. A list of selected stream sites presented with each curve provides information about the sites including river miles, drainage areas, the location of U.S. Geological Survey stream flowgage stations, and the location of streams Abstract crossing hydro logic region boundaries or the Des Moines Lobe landforms region boundary. Two examples are presented for determining river-mile and MCS values, and two techniques are presented for computing flood-frequency discharges.

Counterfactuals and causal inference: Methods and principles for social research

"Most quantitative empirical analyses are motivated by the desire to estimate the causal effect of an independent variable on a dependent variable. Although the randomized experiment is the most powerful design for this task, in most social science research done outside of psychology, experimental designs are infeasible. (Winship & Morgan, 1999, p. 659)." This quote from earlier work by Winship and Morgan, which was instrumental in setting the groundwork for their book, captures the essence of our review of Morgan and Winship's book: It is about causality in nonexperimental settings.