Economic development, enlightenment and creative transformation : creative industries in the New China

This paper examines some of the implications for China of the creative industries agenda as drawn by some recent commentators. The creative industries have been seen by many commentators as essential if China is to move from an imitative low-value economy to an innovative high value one. Some suggest that this trajectory is impossible without a full transition to liberal capitalism and democracy - not just removing censorship but instituting 'enlightenment values'. Others suggest that the development of the creative industries themselves will promote social and political change. The paper suggests that the creative industries takes certain elements of a prior cultural industries concept and links it to a new kind of economic development agenda. Though this agenda presents problems for the Chinese government it does not in itself imply the kind of radical democratic political change with which these commentators associate it. In the form in which the creative industries are presented – as part of an informational economy rather than as a cultural politics – it can be accommodated by a Chinese regime doing ‘business as usual’.

The geography of creative people in Germany

It has been argued that creativity is an important source of regional growth. This paper investigates the geography of people in creative occupation in Germany. The population share of the Creative Class as well as of bohemians and artists is relatively high in larger cities, but smaller places and rural regions may also have a considerable proportion of people with a creative job. While ethnical and cultural diversity and a high level of public supply in health care and education can explain the distribution of creative people, employment opportunities seem to play only a minor role. A high share of creative occupations seems to be conducive to regional growth; however, the exact nature of this relationship is still unclear.

Die Geographie der Kreativen Klasse in Deutschland [The geography of the Creative Class in Germany]

We analyze the regional distribution of different categories of creative individuals in Germany. Generally, the share of creative people is higher in cities as compared to the rural area The freelancing artists are a kind of exception in this respect; they constitute a relatively high share of the population in some rural area A high share of creative people in a region can be explained by a high level of public provisions and a high share of foreign born population, which can be regarded as an indicator of the “openness” in the local milieu. Good employment opportunities have only a relatively weak impact. Regions with a high share of creatives tend to have an above average level of new business formation, a high level of innovation and a relatively high share of employees in high-tech industries.

Endogenous mortality, human capital and economic growth

We consider growth and welfare effects of lifetime-uncertainty in an economy with human capital-led endogenous growth. We argue that lifetime uncertainty reduces private incentives to invest in both physical and human capital. Using an overlapping generations framework with finite-lived households we analyze the relevance of government expenditure on health and education to counter such growth-reducing forces. We focus on three different models that differ with respect to the mode of financing of education: (i) both private and public spending, (ii) only public spending, and (iii) only private spending. Results show that models (i) and (iii) outperform model (ii) with respect to long-term growth rates of per capita income, welfare levels and other important macroeconomic indicators. Theoretical predictions of model rankings for these macroeconomic indicators are also supported by observed stylized facts.

Evaluating multivariate volatility forecasts : how effective are statistical and economic loss functions?

Multivariate volatility forecasts are an important input in many financial applications, in particular portfolio optimisation problems. Given the number of models available and the range of loss functions to discriminate between them, it is obvious that selecting the optimal forecasting model is challenging. The aim of this thesis is to thoroughly investigate how effective many commonly used statistical (MSE and QLIKE) and economic (portfolio variance and portfolio utility) loss functions are at discriminating between competing multivariate volatility forecasts. An analytical investigation of the loss functions is performed to determine whether they identify the correct forecast as the best forecast. This is followed by an extensive simulation study examines the ability of the loss functions to consistently rank forecasts, and their statistical power within tests of predictive ability. For the tests of predictive ability, the model confidence set (MCS) approach of Hansen, Lunde and Nason (2003, 2011) is employed. As well, an empirical study investigates whether simulation findings hold in a realistic setting. In light of these earlier studies, a major empirical study seeks to identify the set of superior multivariate volatility forecasting models from 43 models that use either daily squared returns or realised volatility to generate forecasts. This study also assesses how the choice of volatility proxy affects the ability of the statistical loss functions to discriminate between forecasts. Analysis of the loss functions shows that QLIKE, MSE and portfolio variance can discriminate between multivariate volatility forecasts, while portfolio utility cannot. An examination of the effective loss functions shows that they all can identify the correct forecast at a point in time, however, their ability to discriminate between competing forecasts does vary. That is, QLIKE is identified as the most effective loss function, followed by portfolio variance which is then followed by MSE. The major empirical analysis reports that the optimal set of multivariate volatility forecasting models includes forecasts generated from daily squared returns and realised volatility. Furthermore, it finds that the volatility proxy affects the statistical loss functions’ ability to discriminate between forecasts in tests of predictive ability. These findings deepen our understanding of how to choose between competing multivariate volatility forecasts.

An economic evaluation of the Safe Motherhood programme in Guangxi, China

Maternal and infant mortality is a global health issue with a significant social and economic impact. Each year, over half a million women worldwide die due to complications related to pregnancy or childbirth, four million infants die in the first 28 days of life, and eight million infants die in the first year. Ninety-nine percent of maternal and infant deaths are in developing countries. Reducing maternal and infant mortality is among the key international development goals. In China, the national maternal mortality ratio and infant mortality rate were reduced greatly in the past two decades, yet a large discrepancy remains between urban and rural areas. To address this problem, a large-scale Safe Motherhood Programme was initiated in 2000. The programme was implemented in Guangxi in 2003. Interventions in the programme included both demand-side and supply side-interventions focusing on increasing health service use and improving birth outcomes. Little is known about the effects and economic outcomes of the Safe Motherhood Programme in Guangxi, although it has been implemented for seven years. The aim of this research is to estimate the effectiveness and cost-effectiveness of the interventions in the Safe Motherhood Programme in Guangxi, China. The objectives of this research include: 1. To evaluate whether the changes of health service use and birth outcomes are associated with the interventions in the Safe Motherhood Programme. 2. To estimate the cost-effectiveness of the interventions in the Safe Motherhood Programme and quantify the uncertainty surrounding the decision. 3. To assess the expected value of perfect information associated with both the whole decision and individual parameters, and interpret the findings to inform priority setting in further research and policy making in this area. A quasi-experimental study design was used in this research to assess the effectiveness of the programme in increasing health service use and improving birth outcomes. The study subjects were 51 intervention counties and 30 control counties. Data on the health service use, birth outcomes and socio-economic factors from 2001 to 2007 were collected from the programme database and statistical yearbooks. Based on the profile plots of the data, general linear mixed models were used to evaluate the effectiveness of the programme while controlling for the effects of baseline levels of the response variables, change of socio-economic factors over time and correlations among repeated measurements from the same county. Redundant multicollinear variables were deleted from the mixed model using the results of the multicollinearity diagnoses. For each response variable, the best covariance structure was selected from 15 alternatives according to the fit statistics including Akaike information criterion, Finite-population corrected Akaike information criterion, and Schwarz.s Bayesian information criterion. Residual diagnostics were used to validate the model assumptions. Statistical inferences were made to show the effect of the programme on health service use and birth outcomes. A decision analytic model was developed to evaluate the cost-effectiveness of the programme, quantify the decision uncertainty, and estimate the expected value of perfect information associated with the decision. The model was used to describe the transitions between health states for women and infants and reflect the change of both costs and health benefits associated with implementing the programme. Result gained from the mixed models and other relevant evidence identified were synthesised appropriately to inform the input parameters of the model. Incremental cost-effectiveness ratios of the programme were calculated for the two groups of intervention counties over time. Uncertainty surrounding the parameters was dealt with using probabilistic sensitivity analysis, and uncertainty relating to model assumptions was handled using scenario analysis. Finally the expected value of perfect information for both the whole model and individual parameters in the model were estimated to inform priority setting in further research in this area.The annual change rates of the antenatal care rate and the institutionalised delivery rate were improved significantly in the intervention counties after the programme was implemented. Significant improvements were also found in the annual change rates of the maternal mortality ratio, the infant mortality rate, the incidence rate of neonatal tetanus and the mortality rate of neonatal tetanus in the intervention counties after the implementation of the programme. The annual change rate of the neonatal mortality rate was also improved, although the improvement was only close to statistical significance. The influences of the socio-economic factors on the health service use indicators and birth outcomes were identified. The rural income per capita had a significant positive impact on the health service use indicators, and a significant negative impact on the birth outcomes. The number of beds in healthcare institutions per 1,000 population and the number of rural telephone subscribers per 1,000 were found to be positively significantly related to the institutionalised delivery rate. The length of highway per square kilometre negatively influenced the maternal mortality ratio. The percentage of employed persons in the primary industry had a significant negative impact on the institutionalised delivery rate, and a significant positive impact on the infant mortality rate and neonatal mortality rate. The incremental costs of implementing the programme over the existing practice were US $11.1 million from the societal perspective, and US $13.8 million from the perspective of the Ministry of Health. Overall, 28,711 life years were generated by the programme, producing an overall incremental cost-effectiveness ratio of US $386 from the societal perspective, and US $480 from the perspective of the Ministry of Health, both of which were below the threshold willingness-to-pay ratio of US $675. The expected net monetary benefit generated by the programme was US $8.3 million from the societal perspective, and US $5.5 million from the perspective of the Ministry of Health. The overall probability that the programme was cost-effective was 0.93 and 0.89 from the two perspectives, respectively. The incremental cost-effectiveness ratio of the programme was insensitive to the different estimates of the three parameters relating to the model assumptions. Further research could be conducted to reduce the uncertainty surrounding the decision, in which the upper limit of investment was US $0.6 million from the societal perspective, and US $1.3 million from the perspective of the Ministry of Health. It is also worthwhile to get a more precise estimate of the improvement of infant mortality rate. The population expected value of perfect information for individual parameters associated with this parameter was US $0.99 million from the societal perspective, and US $1.14 million from the perspective of the Ministry of Health. The findings from this study have shown that the interventions in the Safe Motherhood Programme were both effective and cost-effective in increasing health service use and improving birth outcomes in rural areas of Guangxi, China. Therefore, the programme represents a good public health investment and should be adopted and further expanded to an even broader area if possible. This research provides economic evidence to inform efficient decision making in improving maternal and infant health in developing countries.

Right to the city, desire for the suburb?

The 2000s have been a lively decade for cities. The Worldwatch Institute estimated that 2007 was the first year in human history that more people worldwide lived in cities than the countryside. Globalisation and new digital media technologies have generated the seemingly paradoxical outcome that spatial location came to be more rather than less important, as combinations of firms, industries, cultural activities and creative talents have increasingly clustered around a select node of what have been termed “creative cities,” that are in turn highly networked into global circuits of economic capital, political power and entertainment media. Intellectually, the period has seen what the UCLA geographer Ed Soja refers to as the spatial turn in social theory, where “whatever your interests may be, they can be significantly advanced by adopting a critical spatial perspective”. This is related to the dynamic properties of socially constructed space itself, or what Soja terms “the powerful forces that arise from socially produced spaces such as urban agglomerations and cohesive regional economies,” with the result that “what can be called the stimulus of socio-spatial agglomeration is today being assertively described as the primary cause of economic development, technological innovation, and cultural creativity”

Why evolutionary realism underpins evolutionary economic analysis and theory

This paper offers a reply to Jochen Runde's critical appraisal of the ontological framework underpinning Dopfer and Potts's (2008) General Theory of Economic Evolution. We argue that Runde's comprehensive critique contains several of what we perceive to be misunderstandings in relation to the key concepts of ‘generic’ and ‘meso’ that we seek here to unpack and redress.

School education as social and economic governance : responsibilising communities through industry-school engagement

This article examines shifts in educational and social governance taking place in Queensland, Australia, through Industry School Engagement Strategy of Education Queensland and its Gateway Schools program. This significant educational initiative is set within the context of the social investment agenda first articulated in the education policy framework, Queensland State Education-2010. The article traces the historic extension of this governmental strategy through establishment of the Gateway Schools concept that brokers industry-school partnerships with global players in the Queensland economy. Industry sectors forming the partnerships include Minerals and Energy, Aerospace, Wine Tourism, Agribusiness, Manufacturing and Engineering, Building and Construction and ICT. We argue that this ‘post-bureaucratic’ model of schooling represents a new social settlement of neoliberal governance, in which educational outcomes align with economic objectives, and frame the conditions for community self-governance.

Social Procurement: Promoting the sustainability of NPOs through the transformation of economic, social and cultural capital

Social procurement provides a key source of income for the Third Sector, and is vital for the sustainability of many nonprofit organisations. Social procurement involves the exchange of economic capital from one organisation, typically government (although for-profit and non-profit organisations can also purchase), with a nonprofit organisations in order to deliver other forms of. It is this transformation of economic capital into other forms of capital (cultural, human, social) in the social procurement process, which is the focus of this paper. Four case studies, which are representative of the four main types of social procurement, will be examined in order to trace how economic capital is transformed into other types of capital in each of these cases. In so doing, the paper will advance our understanding of social procurement theoretically, and lead to a wider discussion about the role of social procurement in ensuring the sustainability of nonprofit organisations, and the civil societies in which they operate.