Voluntary Adopters of Integrated Reporting – Evidence on Forecast Accuracy and Firm Value

This study investigates how integrated reporting (IR) creates value for investors. It examines how providers of financial capital benefit from an improved firm information environment provided by IR. Specifically, this study investigates the effect of voluntary IR disclosure on analyst earnings forecast accuracy as well as on firm value. To do so, we use an international sample of 167 listed companies that voluntarily publish an integrated report. Our analysis shows no significant effect of a voluntary IR publication on analyst earnings forecast accuracy and no significant effect on firm value. We thus do not find evidence for the fulfillment of IR's promises regarding improved information environment and value creation of voluntary adopters. We conclude that such companies might already have a relatively high level of transparency leading to an absent additional effect of IR disclosure. Positive effects of IR appear to be more relevant in environments where IR is mandatory.     

Effets des conceptions de l'erreur,de la motivation à apprendre et du soutien social sur l'intention de transférer les nouveaux apprentissages : un modèle de médiation modérée

This study aims to assess whether trainees' errors orientation can influence their motivation to learn and their intention to transfer learning. Data were collected from 275 trainees participating in a corporate training program offered by a Canadian government agency. Results show that the concept of learning by error positively influences trainees' levels of motivation and their intention to transfer learning. Results also confirm the mediating role motivation plays between the concept of learning by error and the intention of transferring learning. Finally, results confirm the moderating role of social support on the relationship between motivation to learn and the intention to transfer learning. Practical and theoretical implications of these results are discussed. Copyright © 2017 ASAC. Published by John Wiley & Sons, Ltd.     

Does money have a role in the inflation process? Evidence from Australia

Inflation, defined as a sustained increase in the price level, is considered a monetary phenomenon, as it can be explained within the framework of money‐demand and money‐supply relationships. In the extant literature, money growth is shown to remain causally related to inflation across countries and over time, irrespective of the exchange rate regime and stability of the money‐demand function. Nevertheless, emerging literature suggests a diminishing role of money in the conduct of monetary policy for price stability, especially under inflation targeting. Monetary policy in Australia under inflation targeting since 1993 is an example of policy that denies a relationship between money growth and inflation. The proposition that money does not matter insofar as inflation is concerned seems odd in both theory and the best‐practice monetary policy for price stability. This paper uses annual data for the period 1970–2017 and quarterly data for the period 1970Q1–2015Q1. It deploys both the Johansen cointegration approach and the autoregressive distributed lag (ARDL) cointegration approach to investigate for Australia whether money, real output, prices and the exchange rate (non‐stationary variables) maintain the long‐run price‐level relationship that the classical monetary theory suggests in the presence of such stationary variables as the domestic and foreign interest rates. As expected, the empirical findings for Australia are consistent with the classical long‐run price‐level relationship between money, real output, prices and the exchange rate. The error‐correction model of inflation confirms the presence of a cointegral relationship among these variables; it also provides strong evidence of a short‐run causal relationship between money supply growth and inflation. On the basis of a priori theoretical predictions and empirical findings, the paper draws the conclusion that the monetary aggregate and its growth rate matter insofar as inflation is concerned, irrespective of the strategy of monetary policy for price stability.     

Dynamic price discovery in Chinese agricultural futures markets

Research has not fully explored how Chinese agricultural futures markets perform their price discovery function over time. Our paper examines the role of Chinese agricultural futures markets in the price discovery process based on three well-established measurements of average price discovery contribution, and more importantly, the dynamic price discovery measurement. Using daily futures and spot prices from fourteen agricultural commodities, we find eleven contracts are efficient in price discovery. Besides, market-oriented changes in policies strengthen the price discovery performance of most futures markets, except for commodities that rely heavily on imports from other countries. Our results also suggest that trading activity is particularly important in determining whether thinly traded contracts are efficient in price discovery. Our paper provides a comprehensive judgment involving both average and dynamic price discovery contribution measurements on assessing the efficiency of Chinese agricultural futures markets. Our results might also serve as a reminder that market-oriented reforms in the spot markets of commodities might be useful to intensify the pricing power of the futures markets.     

BALANCED VARIABLE ADDITION IN LINEAR MODELS

This paper studies what happens when we move from a short regression to a long regression in a setting where both regressions are subject to misspecification. In this setup, the least‐squares estimator in the long regression may have larger inconsistency than the least‐squares estimator in the short regression. We provide a simple interpretation for the comparison of the inconsistencies and study under which conditions the additional regressors in the long regression represent a “balanced addition” to the short regression.     

Mixed random forest,cointegration, and forecasting gasoline prices

One of the most successful forecasting machine learning (ML) procedures is random forest (RF). In this paper, we propose a new mixed RF approach for modeling departures from linearity that helps identify (i) explanatory variables with nonlinear impacts, (ii) threshold values, and (iii) the closest parametric approximation. The methodology is applied to weekly forecasts of gasoline prices, cointegrated with international oil prices and exchange rates. Recent specifications for nonlinear error correction (NEC) models include threshold autoregressive models (TAR) and double-threshold smooth transition autoregressive (STAR) models. We propose a new mixed RF model specification strategy and apply it to the determinants of weekly prices of the Spanish gasoline market from 2010 to 2019. In particular, the mixed RF is able to identify nonlinearities in both the error correction term and the rate of change of oil prices. It provides the best weekly gasoline price forecasting performance and supports the logistic error correction model (ECM) approximation.     

ICT investment and GDP growth: Causality analysis for the case of Korea

This study investigated how investment in the industry of Information, Communication and Technology (ICT) has been interlocked with the GDP growth of South Korea. Based on seasonally-adjusted quarterly time-series data for the period between 1999 and 2016 available from the Korea Statistical Information Service, a Vector Error Correction model was applied for the analysis. The results revealed that ICT investment and GDP growth affected bi-directionally except for the short-run case in which only ICT investment affected GDP growth. The results explain that ICT investment plays an important role in the economic growth of South Korea in the long term; at the same time, investment size in the ICT industry increases as the economy grows. Without controlling any other factors, we found GDP increases by 0.4% when ICT investment increases by 1%. However, in the short term, only ICT leads to GDP growth. Therefore, the recent stagnation in ICT investment experienced in South Korea could negatively affect the economic growth of Korea in the short run, and hence, in the long-run, if it should become prolonged. The ICT investment strategy revealed from this study is especially useful to policy-makers who plan the economic growth in South Korea and other ICT-advanced countries because promoting ICT utilization across all sectors requires putting legal and policy mechanisms in place.     

创新测量误差：理论框架与研究展望

创新测量误差会严重影响学术研究、政策制定与企业决策质量，且相关问题研究缺乏清晰的逻辑主线与理论框架。通过查阅国内外研究文献，围绕什么是创新测量误差、为何产生创新测量误差以及如何减少创新测量误差的逻辑主线进行系统梳理与分析，建立创新测量误差研究理论框架，得出相应研究结论并对未来研究方向进行展望，以期为创新实践提供有益参考与借鉴。