On the real-time predictive content of financial condition indices for growth

We provide evidence on the real-time predictive content of the National Financial Conditions Index (NFCI), for conditional quantiles of U.S. real GDP growth. Our work is distinct from the literature in two specific ways. First, we construct (unofficial) real-time vintages of the NFCI. This allows us to conduct out-of-sample analysis without introducing the kind of look-ahead biases that are naturally introduced when using a single current vintage. We then develop methods for conducting asymptotic inference on tests of equal tick loss between nested quantile regression models when the data are subject to revision. We conclude by evaluating the real-time predictive content of NFCI vintages for quantiles of real GDP growth. While our results largely reinforce the literature, we find gains to using real-time vintages leading up to recessions—precisely when policymakers need such a monitoring device.     

Open economy forecasting with a DSGE-VAR: Head to head with the RBNZ published forecasts

We construct a DSGE-VAR model for competing head to head with the long history of published forecasts of the Reserve Bank of New Zealand. We also construct a Bayesian VAR model with a Minnesota prior for forecast comparison. The DSGE-VAR model combines a structural DSGE model with a statistical VAR model based on the in-sample fit over the majority of New Zealand’s inflation-targeting period. We evaluate the real-time out-of-sample forecasting performance of the DSGE-VAR model, and show that the forecasts from the DSGE-VAR are competitive with the Reserve Bank of New Zealand’s published, judgmentally-adjusted forecasts. The Bayesian VAR model with a Minnesota prior also provides a competitive forecasting performance, and generally, with a few exceptions, out-performs both the DSGE-VAR and the Reserve Bank’s own forecasts.     

Monetary policy announcements and stock reactions: An international comparison

This article investigates the impact of domestic monetary policy rate announcements on the stock markets of New Zealand, Australia, the United Kingdom and the euro area, using event-study methods to identify stock price reactions to the unanticipated/surprise component of announcements. As Australia and New Zealand did not reach the zero bound we investigate whether there is an impact from the global financial crisis on stock market reactions that can be distinguished from the asymmetric reactions to surprises that characterise the business cycle. We find that the euro area and the UK both show a financial crisis effect but behaviour in New Zealand and Australia does not change. We conduct robustness checks and explore confounding factors, especially the impact of ‘guidance’ from central banks that prepares markets for policy rate changes.     

Density forecasting with Bayesian Vector Autoregressive models under macroeconomic data uncertainty

Macroeconomic data are subject to data revisions. Yet, the usual way of generating real-time density forecasts from Bayesian Vector Autoregressive (BVAR) models makes no allowance for data uncertainty from future data revisions. We develop methods of allowing for data uncertainty when forecasting with BVAR models with stochastic volatility. First, the BVAR forecasting model is estimated on real-time vintages. Second, the BVAR model is jointly estimated with a model of data revisions such that forecasts are conditioned on estimates of the ‘true’ values. We find that this second method generally improves upon conventional practice for density forecasting, especially for the United States.     

Human resource strategies,workplace reform and industrial restructuring in Australia and New Zealand

In recent years, Australia and New Zealand have pursued two different routes of labour market reform. New Zealand opted for a radical experiment in the deregulation of industrial relations and other areas. Australia pursued a co-operative and co-ordinated approach to reform within the centralized arbitral system. Both reform initiatives were designed to stimulate improvements in organizational performance and cost competitiveness. In this paper, we argue that there are three main types of strategies that management can use to reduce labour cost and improve performance: productivity-enhancement, costminimization and work-intensification strategies. We argue that the former is a long-term sustainable strategy whereas the latter two are negative short-term strategies that may have deleterious longer-term effects. This paper reports the results of a cross-national survey in New Zealand and Australia into the extent of adoption of these management strategies. The results are presented by industry, employment size, mode of operation and countries as a whole. The research findings indicate that New Zealand's decentralization has encouraged a higher degree of employer experimentation with both positive and negative workplace change strategies, especially in the private sector. Australia's more centralized system limited the use of cost-minimization strategies but not productivity-enhancing strategies in the public and not-for-profit sector. The research found evidence of work intensification in both countries.     

Evolving macroeconomic perceptions and the term structure of interest rates

We explore the role of evolving beliefs regarding the structure of the macroeconomy in improving our understanding of the term structure of interest rates within the context of a simple macro-finance model. Using quarterly vintages of real-time data and survey forecasts for the United States over the past 40 years, we show that a recursively estimated VAR on real GDP growth, inflation and the nominal short-term interest rate generates predictions that are more consistent with survey forecasts than a benchmark fixed-coefficient counterpart. We then estimate a simple term structure model under the assumption that investor risk attitude is driven by near-term expectations of the three state variables. When we allow for evolving beliefs about the macroeconomy, the resulting term structure model provides a better fit to the cross section of yields than the benchmark model, especially at longer maturities, and exhibits better performance in out-of-sample predictions of future yield movements.     

Forecasting recovery rates on non-performing loans with machine learning

We compare the performance of a wide set of regression techniques and machine-learning algorithms for predicting recovery rates on non-performing loans, using a private database from a European debt collection agency. We find that rule-based algorithms such as Cubist, boosted trees, and random forests perform significantly better than other approaches. In addition to loan contract specificities, predictors that refer to the bank recovery process — prior to the portfolio’s sale to a debt collector — are also shown to enhance forecasting performance. These variables, derived from the time series of contacts to defaulted clients and client reimbursements to the bank, help all algorithms better identify debtors with different repayment ability and/or commitment, and in general those with different recovery potential.     

Network embeddedness in the internationalization of biotechnology entrepreneurs

This study investigates how entrepreneurs of biotech enterprises embed in domestic and international networks so as to internationalize. We advance a contextual framework of embeddedness of internationalizing entrepreneurs, providing a contribution (i) by synthesizing and applying existing conceptual insights from the networking literature to provide a more culturally sensitive view of getting embedded for international entrepreneurship in the biotech industry and (ii) by adding insights into the practices and (micro)processes of how and in what ways embeddedness integrates with the internationalization of biotech entrepreneurs. Our study involves six entrepreneurs from Canada, Finland, and New Zealand. Context-specific embeddedness was studied by exploring the (i) type, (ii) strength, (iii) locality, and (iv) importance of the international and national network ties among internationalizing entrepreneurs. We found differences in relation to the locality of universities and research institutes, role and type of financiers, and customer focus in internationalization. For instance, while customers were central to the embeddedness of Canadian and New Zealand entrepreneurs, Finnish entrepreneurs had no focus on their customers, but acted solely through sales channels and partners. The customer focus of New Zealand entrepreneurs was mainly international, whereas it was domestic in the case of Canadian entrepreneurs.     

Voluntary Disclosure in the Annual Reports of New Zealand Companies

New Zealand is currently experiencing a liberal and competitive economic environment which has led to a greater investment interest in corporate securities. Likewise, New Zealand firms are also developing strategies to attract investors, for example, through voluntary disclosure of information. Therefore, the level of information voluntarily disclosed by New Zealand companies is of interest to prospective investors. The purpose of this study is to examine empirically the relationship between five firm-specific characteristics and the general level of accounting information voluntarily disclosed by companies listed on New Zealand Stock Exchange (NZSE). In this study the a priori expectations are based on agency theory. The five firm-specific characteristics examined are: firm size, leverage, assets-in-place, type of auditor, and foreign listing status. The results obtained from cross-sectional regression show that firm size, foreign listing status and leverage are significantly related to the extent of voluntary disclosure. In contrast assets-in-place and type of auditor are not significant explanatory variables. A study of this type would be of particular relevance to accounting policy makers because, inter alia, it helps them in (a) understanding corporate disclosure behaviour, (b) explaining why firms adopt certain disclosure strategies, and (c) developing a coherent and acceptable set of mandatory disclosure requirements.     

Examining the extent of and determinants for sustainability assurance quality: The role of audit committees

This study examines the extent of and determinants for sustainability assurance quality. Data comprise sustainability assurance statements published by the top 100 listed companies in Australia and New Zealand from 2017 to 2019. The findings indicate that Australian companies lead their New Zealand counterparts in sustainability assurance. Although sustainability reporting has risen, assurance rates remain significantly low. Accountants dominate the market, and companies prefer to use their own auditors for sustainability assurance work. Sustainability assurance quality is poor and does not vary significantly among Australian and New Zealand companies. Low-quality sustainability assurance plays a limited role in mitigating potential stakeholder–agency conflicts. The regression analysis indicates that audit committee characteristics such as members' independence, industry/market expertise, and attending meetings enhance sustainability assurance quality, whereas audit committee size has no affect. These findings suggest that audit committee characteristics such as independence, industry expertise, and regular meeting attendance have the potential to reduce stakeholder–agency conflicts by improving the quality of sustainability statement assurance. Our findings build on the sustainability assurance literature by exploring current trends in sustainability assurance practices in Australia and New Zealand where corporate governance codes have been recently revised. Further, these findings are timely given recent changes in standards (International Standard on Assurance Engagements [ISAE] 3000 and Global Reporting Initiative [GRI]). Our study contributes to the audit committee literature and sheds light on the role played by audit committee characteristics on sustainability assurance statement quality. The study findings potentially offer useful insights for practitioners, standard setters, and regulators.     

Earnings cosmetics in a tax-driven accounting environment: evidence from Finnish public firms

Finnish firms are known to manage earnings downwards to avoid income taxes. This study suggests that they simultaneously manage earnings upwards in a smaller scale. The idea behind this behaviour is that humans may perceive a profit of, say, 301 million as abnormally larger than a profit of 298 million. Consequently, firms tend to adjust the second leftmost digit of earnings to exceed nine in order to make the first digit of earnings larger by one. Such corporate behaviour has been previously documented in New Zealand and in the USA. Our study finds a similar phenomenon in Finland. Our results show that although the largest second digits (eight and nine) are fewer than expected, only sixes and sevens are statistically significantly managed upwards.     

Spillover effects on the sectoral returns for australian and New Zealand equity markets

In this paper, we examine the return and volatility spillovers, together with the trend spillovers on the sectoral equity returns for Australian and New Zealand markets. We find that the return spillovers of industrial, local and global shocks have a limited effect on Australian and New Zealand sector returns, whereas the volatility spillovers play a significant role on explaining the volatility of sector equity indices. Furthermore, we discover that the volatility spillover effects of the global and industrial shocks are greater in magnitude for explaining the volatility of the Australian sectors than those of New Zealand, particularly basic materials, oil and gas, technology and telecom sectors. By employing the trend spillover model, we find that the volatility spillover effects of global sector indices have been increasing over the volatility of the Australian sectoral returns until now. This finding proposes that Australian sector equity market is more integrated with the world than the New Zealand counterpart.     

Comparing the accuracy of several network-based COVID-19 prediction algorithms

Researchers from various scientific disciplines have attempted to forecast the spread of coronavirus disease 2019 (COVID-19). The proposed epidemic prediction methods range from basic curve fitting methods and traffic interaction models to machine-learning approaches. If we combine all these approaches, we obtain the Network Inference-based Prediction Algorithm (NIPA). In this paper, we analyse a diverse set of COVID-19 forecast algorithms, including several modifications of NIPA. Among the algorithms that we evaluated, the original NIPA performed best at forecasting the spread of COVID-19 in Hubei, China and in the Netherlands. In particular, we show that network-based forecasting is superior to any other forecasting algorithm.     

The implementation of monetary policy in New Zealand: What factors affect the 90-day bank bill rate?

This paper discusses the implementation of monetary policy in New Zealand and its flow-on effects on the 90-day bank bill rate over the 1999–2005 period. The effects of external factors are considered as well. Our findings indicate that the maturity spectrum ratio exerted a positive effect on the 90-day bank bill rate while the allotment ratio did not. This interest rate had a tendency to revert to the level set by its Australian counterpart, though at a relatively slow speed. No such link exists between the NZ 90-day rate and the U.S. 90-day rate. Neither the maturity spectrum nor the allotment ratio contributed to the volatility of the most important short-term interest rate in New Zealand.     

Time-Varying Relationship between Inflation and Inflation Uncertainty

This paper investigates whether the relationship between inflation and inflation uncertainty has changed and whether the change in this relationship has been gradual or abrupt. We extend the time-varying parameter with stochastic volatility in mean model (TVP-SVM) to include a mixture innovation disturbance in the time-varying parameter process. The proposed model produces more reliable estimates and allows us to investigate the occurrence of breaks in the gradually evolving process of the time varying coefficients. Using data of US, Germany, Canada, New Zealand, UK, France, Italy, Spain and Australia, we find that: (i) the relationship between inflation and inflation uncertainty substantially varies over time; (ii) there is strong support for the existence of abrupt changes in the US inflation–inflation uncertainty relationship; (iii) our empirical results of Canada and New Zealand show that the correlation between inflation and inflation uncertainty has been much weaker since early 1990s, which coincides with the timing of the implementation of inflation targeting.     

Capitalizing Non-cancelable Operating Leases

There have been recent international moves to require the capitalization of non‐cancelable operating leases. Most prior research on the constructive capitalization of leases has been undertaken on US data. The results from US studies may not apply to international firms because non‐US operating lease contracts may differ in lease term, discount rates, and renewal options. This study presents the financial statement impact of constructive capitalization for 38 firms listed on the New Zealand Stock Exchange. New Zealand is an appropriate institutional setting because the required footnote disclosures for operating leases are similar to the International Accounting Standard. The method of constructive capitalization follows the general approach developed by Imhoff, et al. (1991) . The results show that constructive capitalization has a material impact on reported liabilities and financial ratios. The results suggest that, relative to present value procedures of constructive lease capitalization, heuristics used by analysts lead to the overstatement of lease liabilities and lease assets. However, the use of single cross‐sectional parameters (e.g., discount rates, lease life) results in constructed lease assets and liabilities that are similar to more elaborate firm‐specific procedures.     

实时视觉中心技术在低速率视频通信中的应用

文章在对视觉中心技术和视频编码技术进行分析研究的基础上,利用低速率视频编码常采用粗量化的特点,设计并实现了一种快速的实时视觉中心处理算法。该算法将计算复杂度很高的视觉中心处理算法改进为只需简单的查表计算即可完成,从而极大地降低了计算量。实验表明:该方法能提高视频图像的主观质量。     

Forecasting national activity using lots of international predictors: An application to New Zealand

We assess the marginal predictive content of a large international dataset for forecasting GDP in New Zealand, an archetypal small open economy. We apply “data-rich” factor and shrinkage methods to efficiently handle hundreds of predictor series from many countries. The methods covered are principal components, targeted predictors, weighted principal components, partial least squares, elastic net and ridge regression. We find that exploiting a large international dataset can improve forecasts relative to data-rich approaches based on a large national dataset only, and also relative to more traditional approaches based on small datasets. This is in spite of New Zealand’s business and consumer confidence and expectations data capturing a substantial proportion of the predictive information in the international data. The largest forecasting accuracy gains from including international predictors are at longer forecast horizons. The forecasting performance achievable with the data-rich methods differs widely, with shrinkage methods and partial least squares performing best in handling the international data.     

Sustainability practices: trends in New Zealand businesses

This paper reports on the sustainability practices of New Zealand businesses based on two national surveys and a series of focus groups and interviews. There was an average increase of 10% in the number of companies adopting environmental practices from 2003 to 2006. There was less of an increase for social practices, although still more commonly adopted by companies than environmental practices. Values and beliefs of management were the overwhelming driver for the adoption of sustainability practices with reputation and brand also significant drivers. Costs, management time, and knowledge/skills were the three most commonly reported barriers to adoption of sustainability initiatives. The implications of the study are that for New Zealand business, there is a strong link with the business case for sustainability. For policymakers interested in achieving sustainability goals, the results suggest that a ‘soft’ approach to business practices may be in order in New Zealand. Copyright © 2009 John Wiley & Sons, Ltd and ERP Environment.     

Post-script—Retail forecasting: Research and practice

This note updates the 2019 review article “Retail forecasting: Research and practice” in the context of the COVID-19 pandemic and the substantial new research on machine-learning algorithms, when applied to retail. It offers new conclusions and challenges for both research and practice in retail demand forecasting.