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Purpose: The purpose of this paper is to investigate a farm manager's personal characteristics (personality, age, education, objectives, experience, etc.) as drivers of debt payback success and rates. Traditionally bankers have used historic business statistics, and equity levels, to assess loans and credit worthiness. It is hypothesised that a managers' personal characteristics are likely to be a better predictor of future debt payback performance. Design/methodology/approach: The literature was searched to isolate the managers' personal variables likely to determine debt payback. The information led to defining a quantitative model based on the theory of planned behaviour (TPB) which was hypothesised as determining payback rates where a choice was available. A postal random stratified survey of NZ owner operator farm managers provided the data to test the model and define its parameters using regressions, structural equation modelling and statistical comparisons. Findings: The modelling results make it clear a manager's personal characteristics are highly correlated with debt payback and, logically, are very likely to be the drivers. Four random effects equations and a comparison of high- and low-debt payback managers led to this conclusion. Practical implications: Bankers should use the managers' personal characteristics, as defined in the regressions, alongside traditional measures when assessing farm business loan requests. This approach is opposite to the traditional methods using mainly historic data. Originality/value: The use of the TPB in assessing debt payback is a new and novel approach showing how enduring personal characteristics can be used in assessing proposals, and particularly, entrepreneurs' adventurist investments in situations where historic data are not available. [ABSTRACT FROM AUTHOR]

Background: There is a need for accurate and precise food price elasticities (PE, change in consumer demand in response to change in price) to better inform policy on health-related food taxes and subsidies.Methods/design: The Price Experiment and Modelling (Price ExaM) study aims to: I) derive accurate and precise food PE values; II) quantify the impact of price changes on quantity and quality of discrete food group purchases and; III) model the potential health and disease impacts of a range of food taxes and subsidies. To achieve this, we will use a novel method that includes a randomised Virtual Supermarket experiment and econometric methods. Findings will be applied in simulation models to estimate population health impact (quality-adjusted life-years [QALYs]) using a multi-state life-table model. The study will consist of four sequential steps: 1. We generate 5000 price sets with random price variation for all 1412 Virtual Supermarket food and beverage products. Then we add systematic price variation for foods to simulate five taxes and subsidies: a fruit and vegetable subsidy and taxes on sugar, saturated fat, salt, and sugar-sweetened beverages. 2. Using an experimental design, 1000 adult New Zealand shoppers complete five household grocery shops in the Virtual Supermarket where they are randomly assigned to one of the 5000 price sets each time. 3. Output data (i.e., multiple observations of price configurations and purchased amounts) are used as inputs to econometric models (using Bayesian methods) to estimate accurate PE values. 4. A disease simulation model will be run with the new PE values as inputs to estimate QALYs gained and health costs saved for the five policy interventions.Discussion: The Price ExaM study has the potential to enhance public health and economic disciplines by introducing internationally novel scientific methods to estimate accurate and precise food PE values. These values will be used to model the potential health and disease impacts of various food pricing policy options. Findings will inform policy on health-related food taxes and subsidies.Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12616000122459 (registered 3 February 2016). [ABSTRACT FROM AUTHOR]

Introduction and Aims: We investigate the relationship between outlet density (of different types) and violence (as measured by police activity) across the North Island of New Zealand, specifically looking at whether the relationships vary spatially.Design and Methods: We use New Zealand data at the census area unit (approximately suburb) level, on police-attended violent incidents and outlet density (by type of outlet), controlling for population density and local social deprivation. We employed geographically weighted regression to obtain both global average and locally specific estimates of the relationships between alcohol outlet density and violence.Result: We find that bar and night club density, and licensed club density (e.g. sports clubs) have statistically significant and positive relationships with violence, with an additional bar or night club is associated with nearly 5.3 additional violent events per year, and an additional licensed club associated with 0.8 additional violent events per year. These relationships do not show significant spatial variation. In contrast, the effects of off-licence density and restaurant/café density do exhibit significant spatial variation. However, the non-varying effects of bar and night club density are larger than the locally specific effects of other outlet types.Discussion and Conclusion: The relationships between outlet density and violence vary significantly across space for off-licences and restaurants/cafés. These results suggest that in order to minimise alcohol-related harms, such as violence, locally specific policy interventions are likely to be necessary. [Cameron MP, Cochrane W, Gordon C, Livingston M. Alcohol outlet density and violence: A geographically weighted regression approach. Drug Alcohol Rev 2016;35:280-288]. [ABSTRACT FROM AUTHOR]

The article reports that Statistics New Zealand has worked with local business organizations to deliver a series of seminars around New Zealand. Each event, which is open to all business people, advisors and mentors, features a presentation about the local market. The seminars detail how the department's information has helped businesses to evaluate their business potential or estimate their market share.

The article provides data statistics on the biggest companies in Australia and New Zealand which provided information on their climate change programs to the Carbon Disclosure Project (CDP) for 2006. Of the 134 biggest companies, only 60 have furnished detailed information on their climate change programs, while 7% provided some limited information, 19% officially decline to participate and 30% made no response at all. The data gathered from 93% of the companies who responded to the questionnaire in CDP4 revealed the relevance of climate change-related issues to their businesses and 64% identified specific risk and opportunities.