Panel LM unit root tests with level and trend shifts

This paper considers a Lagrange multiplier (LM) based panel unit root test that allows for heterogeneous structural breaks in both the intercepts and slopes of a series. We note that many popular time series variables are likely to exhibit changing means and/or trends over time. Given that the usual tests will depend on the nuisance parameters indicating the locations of the trend breaks, we adopt a transformation procedure that makes our new panel unit root tests invariant to the nuisance parameters. To illustrate the importance of the power gain provided by our test, we examine the convergence hypothesis using relative ratios of per capita health care expenditures in 20 OECD countries. Our results provide evidence that the convergence hypothesis is supported.     

An innovation to improve health outcomes in Amajuba district,KwaZulu-Natal,South Africa

Systems’ thinking places high value on understanding the context. This study focused on the collection of disaggregated data in order to understand the context, to facilitate improvement of health outcomes. The aim of this article was to assess the implementation of municipal ward-based health data collection (disaggregated data) and health care workers’ perceptions of this data collection process. This cross-sectional study used mixed methods in Amajuba district. The participants were professional nurses at the Primary Health Care level. Of the 131 respondents, 123 (93.9%) collected municipal ward-based health data, and found it useful. Opportunities for improving data collection were identified. Disaggregation of the data at ward level contributes to a better understanding of the target population’s health, assists planning for health needs and enables provision of targeted interventions in order to improve health outcomes, to prevent financial regression and waste of health resources.     

Covariance breakdowns and connectedness of crude oil futures markets with non-synchronous data

ABSTRACT

This article identifies the breakdowns in the covariance of three benchmark crude oil futures markets (WTI, Brent and Dubai) and investigates the changes of market connectedness across the breakdown periods. As the crude oil futures are traded in different regions, this article eliminates the non-synchronous trading data by employing the Vector Moving Average structure and the Bayesian data augmentation approach, which keeps the integrity of original data without changing its properties. The results show that there are significant breaks in the covariance structure of crude oil futures markets. The breakdown periods are consistent with the periods when the market volatilities are at high level and the returns are volatile. The changes of market connectedness are independent of the covariance states, which supports the globalization hypothesis for the crude oil market. The results also suggest that there is more information flow out of the WTI than to the WTI during the sample period, particularly during the breakdown periods in 2008–2009.     

Evaluating discounts as a dimension of customer behavior analysis

Today, increased competition between organizations has led them to seek a better understanding of customer behavior through identifying valuable customers. Customers’ expectations about the price and quality of products and services play an important role in their selection process. In online businesses, competition and price differences between suppliers is high, so discounts will attract different customers. As a result, discounts and the frequency and amount of purchases can lead to better understanding of customer behavior. Customer segmentation and analysis is essential for identifying groups of customers. Hence, this study uses a model based on RFM called RdFdMd, in which d is the level of discount used to analyze customer purchase behavior and the importance of discounts on customers’ purchasing behavior and organizational profitability. The CRISP-DM and k-mean algorithm were used for clustering. The results indicate that using the R_dF_dM_d model achieves better customer clustering and valuation, and discounts were identified as an important criterion for customer purchases.     

Industry risk transmission channels and the spillover effects of specific determinants in China’s stock market: A spatial econometrics approach

This paper uses a spatial econometrics approach to study the industry risks in China’s stock market. We comprehensively consider the real linkage and information risk transmission channels and analyze the risk spillovers of specific determinants. Our empirical results show the following: 1) The real linkage channel and information channel are both effective transmission channels for driving spillover effects, and the information channel is of the utmost importance. 2) The spillover effects of specific determinants exist and are persistent. The superposition of spillover effects may lead to extreme risk. 3) The transmission channels and spillover effects are asymmetric in different regimes.     

Crowdsourcing-based semantic relation recognition for natural language questions over RDF data

ABSTRACT

Natural language query systems over RDF data need to rely on the semantic relations in query. First, we propose the new crowdsourcing model that used to produce semantic relations dataset. The model not only inherits completeness of the iterative model and accuracy of the parallel model, but also saves human resources. Second, we mine the rules of semantic relation recognition from the correlations between dependency structures and semantic relations. Third, we propose an algorithm of semantic relation recognition for natural language query over RDF data, and experiments demonstrate that it can recognize more semantic relations than existing methods.     

Media-Based Sentiment Indices as an Alternative Measure of Consumer Confidence

In this paper, we consider the feasibility of constructing online sentiment indices, using large amounts of media data, as an alternative to the conventional survey method used to create the consumer confidence index in South Africa. A clustering framework is adopted to provide an indication of possible candidate sentiment indices constructed from a combination of different text sources and dictionaries that best mimic the traditional survey-based consumer confidence index from the South African Bureau for Economic Research (BER). The results conclude that it is possible to create an index using sentiment analysis using online editorial data that does resemble the BER’s consumer confidence index. The different media-based sentiment indices (MSI) show a significant level of correlation and co-movement with the BER’s CCI. Impulse responses and cross-correlation functions indicate that the MSI could potentially lead the survey-based method up to two quarters. Furthermore, Granger-causality tests show that the media-based indices are good predictors of future consumer confidence index values. The results provide motivation for further study on the use of sentiment-based techniques and online media data sources to track consumer confidence within an emerging market such as South Africa.     

Does corruption slow down innovation? Evidence from a cointegrated panel of U.S. states

I investigate the long-run relationship between corruption and innovative activity using annual data from 48 contiguous U.S. states between 1977 and 2006. Using U.S. data allows me to work with a panel long enough to exploit time series properties of the data. I use two different measures of innovative activity: one measuring the quantity and the other measuring the quality of the patents granted. I also use two different measures of corruption: one based on the number of corruption convictions, the other based on number of corruption stories covered in Associated Press news wires. Following Pedroni (1999, 2000), I estimate the cointegrating relationship between corruption and innovative activity with Fully Modified Ordinary Least Squares (FMOLS). The results indicate that corruption indeed slows down innovation in the long-run.     

Some issues in blockchain for accounting and the supply chain,with an application of distributed databases to virtual organizations

This paper reviews some recent blockchain‐based applications for information capture, distribution and preservation. As part of that review, this paper examines two key concerns with current blockchain designs for accounting and supply chain transactions: data independence and multiple semantic models for the same information distribution problem. Blockchain applications typically integrate database, application and presentation tiers all in the same ledger. This results in a general inability to query information in the ledger and other concerns. Further, since most applications appear to be private blockchain applications, there is a concern of agents needing to accommodate multiple blockchains depending on who their trading partners are and what they request. Finally, this paper uses a distributed database to design a ‘blockchain‐like’ system for virtual organizations.     

In Data We Trust? An Analysis of Indonesian Socioeconomic Survey Data

What if a popular dataset that has generated a large amount of literature has been misunderstood and has led to misleading inferences? This paper examines household expenditure data from the Indonesian National Socio-economic Survey (Susenas), which started more than 50 years ago. Appropriate use of Susenas data for policy analysis requires an understanding that the survey’s expenditure variable does not measure true out-of-pocket expenses, because it includes subsidies received by households when obtaining goods and services. We also highlight an abrupt change in the survey instrument that occurred in 2015, when the reference period for certain items was extended. For health items, this generated a change in the expenditure series that can be misinterpreted as being the result of a social health insurance reform introduced in 2014 to lower the health care burden on households. Accordingly, we propose a way to account for this artificial expenditure movement in Susenas.