Blockchain as the Database Engine in the Accounting System

This paper examines the prediction that blockchain technology will transform accounting and the profession because transactions recorded on a blockchain can be aggregated into financial statements and confirmed as true and accurate. We argue that blockchain technology affects the database engine of the accounting information system (AIS) through digitisation of the current paper‐based validation process. In a blockchain‐based AIS, accountants will no longer be the central authority but will remain the preparer of financial reports required by regulations; they will continue to influence policies such as the choice and accreditation of validators and serve as validators of last resort. Audit evidence still needs to be gathered for rendering of an audit opinion in a blockchain‐based AIS. While digitisation of the validation process reduces the error rate and lowers the cost of vouching and tracing, and immutability of blockchain data reduces the incentive and opportunities for fraud, a blockchain‐based AIS alone does not guarantee that financial reports are true and fair. Lower error rates and reduced incentives for accounting fraud in a blockchain‐based AIS are expected to improve audit quality. This prediction will need to be empirically tested when blockchain‐based AIS become available. Using the three‐tier architecture of the AIS, this paper addresses the gap in the literature that misses how characteristics of blockchain technology can influence the implementation of a blockchain‐based AIS with related implications for the accounting profession.     

The nature of SME co-operation and innovation: A multi-scalar and multi-dimensional analysis

Recent work on SMEs and networks has emphasised the importance of external co-operative ties in enhancing firms’ innovative performance. These external ties provide resource constrained SMEs with access to a wider set of technological opportunities through information sharing and resource pooling. Previous studies of the SME innovation–cooperation relationship have used categorical measures to capture tie existence which, while providing some useful insights, largely fail to capture the strength of co-operative relationships and/or the variety of relational directions in which co-operation occurs. This study aims to address this measurement deficiency and explore the SME innovation–cooperation relationship by designing and utilising measures that capture both the multi-scalar (strength) and multi-dimensional (variety) nature of co-operation and innovation. We then apply these measures to a survey of UK manufacturing SMEs. Data is obtained for 371 SMEs, and we then assess the innovation–co-operation relationship within a multivariate regression framework. We find that the strength of cooperative ties across a range of productive activities within the value chain are important facilitators for SME innovative capability; this is true for both product and process innovation. However, we find that SME co-operation with rivals (co-opetition) has no significant impact upon innovation. Our results have significant implications for both supply chain managers and policy-makers interested in enhancing innovation among SMEs. In particular, we argue that SME innovative activity benefits from good, close dyadic relations within the supply chain, while more generally policy should be geared towards nurturing and sustaining SME innovation networks.     

Primary school students' interests in STEM careers: how conceptions of STEM professionals and gender moderation influence

International Journal of Technology and Design Education - This study assessed elementary school students’ conceptions of STEM professions and its potential influence on STEM career interest,...     

The influence of oil price uncertainty on stock liquidity

Using high-frequency intraday data, this study provides strong empirical evidence that elevated oil price uncertainty has a significant and negative influence on stock liquidity. More specifically, the results suggest that large oil-related corporations are most affected, followed by small-listed firms more generally. Further analysis reveals that liquidity providers widen the bid-ask spreads to protect themselves during periods of high oil price uncertainty for large-listed firms, particularly those in the oil industry. These findings are robust to various measures of oil price uncertainty, different market conditions, structural break analysis and show the influence of oil price movements extends to stock liquidity.     

The market distortion effects of mortgage tightening and transaction taxes: Evidence from Hong Kong residential resale market

By using transaction-level data, we study if two popular policies intended to cool an overheated housing market would serve their intended purposes. We found both mortgage tightening and Special Stamp Duties (SSD) actually led to higher starter home prices in Hong Kong. Mortgage tightening shifted the demand for bigger homes to that for smaller ones. The SSD that applies to resales within a specified period of the original purchase lowered turnover across the housing market. The decline in turnover is, as expected, sharpest for small flats, implying a dramatic shrinkage in second-hand supply of such homes, driving their prices up. We also found transactions bunching as many homes are held till the SSD is no longer applicable, indicating lock-in effects. Relative to those that are not subject to the SSD, the prices of properties subject to the levy are found to be lower by 6.8%.     

A robust textual analysis of the dynamics of Hong Kong property market

Market sentiments influence the dynamics of Hong Kong’s macro-critical property market, but the unobservable nature of market sentiments makes it difficult to systemically assess this sentiment channel. Using text mining techniques, this paper sets up a news-based property market sentiment index and a Google Trends-based buyer incentive index for Hong Kong and studies the sentiment channel of transmission in the Hong Kong property market. The news-based property market sentiment index can reflect the change in sentiments in past key events, with the sentiments in the primary market tending to lead that of the secondary market during the low housing supply period. For the Google Buyer Incentive Index, we find that it has value-added in forecasting (or nowcasting) the official property price index. In mapping out the sentiment channel using a structural vector-autoregressive model, we find that an improvement in market sentiments could stimulate buyers’ incentives, which then together would affect property prices and transaction volumes.     

Threshold estimation for continuous three-phase polynomial regression models with constant mean in the middle regime

This paper considers a continuous three-phase polynomial regression model with two threshold points for dependent data with heteroscedasticity. We assume the model is polynomial of order zero in the middle regime, and is polynomial of higher orders elsewhere. We denote this model by ${ℳ}_2$, which includes models with one or no threshold points, denoted by ${ℳ}_1$ and ${ℳ}_0$, respectively, as special cases. We provide an ordered iterative least squares (OiLS) method when estimating ${ℳ}_2$ and establish the consistency of the OiLS estimators under mild conditions. When the underlying model is ${ℳ}_1$ and is $(d_0-1)$th-order differentiable but not $d_0$th-order differentiable at the threshold point, we further show the $O_p(N^{-1/(d_0+2)})$ convergence rate of the OiLS estimators, which can be faster than the $O_p(N^{-1/(2d_0)})$ convergence rate given in Feder when $d_0\ge 3$. We also apply a model-selection procedure for selecting ${ℳ}_{\kappa }$; $\kappa =0,1,2$. When the underlying model exists, we establish the selection consistency under the aforementioned conditions. Finally, we conduct simulation experiments to demonstrate the finite-sample performance of our asymptotic results.     

The Economics of the Greenium: How Much is the World Willing to Pay to Save the Earth?

Environmental and Resource Economics - Sadly, not much. This paper provides a theoretical and empirical analysis of the greenium, the price premium the investor pays for green bonds over...     

Risk preference interactions between individual farmers and small farmer groups: Experimental evidence from rural Ethiopia

The understanding of risk preference interactions among poor farmers in developing countries has important policy implications, as many programs that aim to alleviate poverty and address risk constraints are provided on a collective basis. We conduct a randomized field experiment in the drought-prone parts of Northern Ethiopia and elicit from poor, vulnerable farmers their hypothetical willingness to pay using individual and group lottery games. Analyzing the certainty equivalent ratios (CERs), we find that farmer groups are more risk averse than individual farmers. When the risk of the lottery is high, the group CER is primarily determined by the most-risk-averse farmer of the group, and to a lesser extent, by the least. The median farmer contributes to the group CER only when the lottery risk is moderate. After participating in the group elicitation, individual farmers also become as risk averse as the group on average. Specifically, the median and the least-risk-averse farmers become significantly more risk averse while the most-risk-averse farmer is unaffected. Our results show that policymakers should carefully consider how social interactions in rural communities affect individual and group risk preference and whether social interactions also affect the participation and effectiveness of development programs.     

Technical progress and induced innovation in China: a variable profit function approach

Journal of Productivity Analysis - We propose a new methodology to estimate empirically the input price-induced technical change and total factor productivity (TFP) growth in China. Our primary...