The case for freedom revisited

I argue that the case for freedom is about either knowledge or incentives. Freedom optimises the production and use of knowledge, and gives people the right incentives. I trace the history of these arguments. Knowledge‐based justifications can be found in the writings of Adam Smith, Jeremy Bentham, Wilhelm von Humboldt, J. S. Mill, Friedrich von Hayek, and Karl Popper. Incentive‐based arguments are due to Thomas Aquinas, Adam Smith, and James Mill. I then go on to query the extent to which classical freedom is compatible with other aims such as efficiency, enforcement of contracts, freedom of choice, political participation, and the socialist concept of freedom. Finally, I reject natural selection as a justification of freedom or of the right of property.     

Structural change,the push-pull hypothesis and the Spanish labour market

This paper proposes a small-scale general equilibrium model of structural transformation with a non-agricultural labour market characterized by search frictions. The model is used to investigate the role of sectoral TFPs as main drivers of structural change and a new growth accounting exercise allows a quantitative reassessment of the importance of the labour reallocation bonus in structural transformation in the presence of labour market frictions. The model is calibrated to data for post-war Spain and its transition from dictatorship to democracy. Counterfactual simulations point towards productivity improvements in agriculture as the main driver, while modifications in labour market institutions affect mainly the labour market itself, with only a modest effect on structural change.     

eHealth in Egypt: The demand-side perspective of implementing electronic health records

The present study sheds light on the expected factors that would impact the adoption of the Electronic Health Records (EHR) service in Egypt from the demand-side perspective, i.e. the healthcare consumer's standpoint. This empirical study is motivated by the use of EHR in many countries as a method of promoting healthcare services. Another incentive for the present study is to look at EHR as a top layer in the Next Generation of Information Infrastructure (NII). EHR is considered an efficiency-enhancing and cost-effective technology. Moreover, the issue of developing the healthcare sector in Egypt has the attention of government policymakers, who have a comprehensive healthcare and social insurance law that will be discussed in the Egyptian Parliament, in the near future. The study highlights the socio-technical approach used in analyzing the EHR as an eHealth application in Egypt. The underlying theoretical framework of this study implicates the Unified Theory of Acceptance and Use of Technology in the Consumer Context (UTAUT2) model. It also applies an integrated framework of multifaceted perceptions used to explain the expected adoption or behavior of the Egyptian consumer vis-à-vis EHR. The study relies on primary data collected after surveying 559 respondents. Results reveal that determinants of EHR include demographics such as place and gender, but more importantly constructs such as price value, effort expectancy and facilitating conditions are key factors that play a part in the decision made by the Egyptian consumer to adopt EHR technology. Finally, additional insight and recommendations are offered to the policymakers.     

Interconnectedness and systemic risk in the US CDS market

This study assesses systemic risk in the US credit default swap (CDS) market. First, this study estimates the bilateral exposures matrix using aggregate fair value data and theoretically analyze interconnectedness in the US CDS network using various network measures. Second, this study theoretically analyzes the contagious defaults. The default analysis shows the theoretical occurrence of many stand-alone defaults and one contagious default via the CDS network during the global financial crisis. A stress test based on a hypothetical severe stress scenario predicts almost no future contagious defaults. Thus, risk contagion via the CDS network is unlikely.     

In search of meaning: Lessons,resources and next steps for computational analysis of financial discourse

We critically assess mainstream accounting and finance research applying methods from computational linguistics (CL) to study financial discourse. We also review common themes and innovations in the literature and assess the incremental contributions of studies applying CL methods over manual content analysis. Key conclusions emerging from our analysis are: (a) accounting and finance research is behind the curve in terms of CL methods generally and word sense disambiguation in particular; (b) implementation issues mean the proposed benefits of CL are often less pronounced than proponents suggest; (c) structural issues limit practical relevance; and (d) CL methods and high quality manual analysis represent complementary approaches to analyzing financial discourse. We describe four CL tools that have yet to gain traction in mainstream AF research but which we believe offer promising ways to enhance the study of meaning in financial discourse. The four tools are named entity recognition (NER), summarization, semantics and corpus linguistics.     

The Endogeneity of Trading Volume in Stock and Bond Returns: An Instrumental Variable Approach

This paper investigates the joint determination of trading volume and returns. Our approach follows from the argument that trading activity depends on security returns, thus resulting in a reverse causality from returns to trading activity. Using exogenous instruments for security trading activity, we estimate a system of two‐stage simultaneous equations to better model the return‐volume relationship. Our results confirm that returns and trading volume are determined simultaneously in both stock and corporate bond markets and that conclusions about the direction and significance of causality between volume and returns can be reversed once one corrects for the endogeneity of volume.     

Time-varying comovement and changes of comovement structure in the Chinese stock market: A causal network method

The driving force for the comovement in stock returns is a long-standing debate between classical asset pricing theory and behavioral finance theory. It has become critically important recently for understanding systemic risk and risk contagion in the market. In this study, we propose complex networks enabled new methods to measure the causal comovement of individual stocks and the comovement structure of the market, which facilitate the examination of all kinds of hypotheses of comovement theories in a unified framework. Using a sample of the Chinese stock market from Jan. 1, 2006 to Dec. 31, 2016, we find that the degree of comovement generally intensifies over time, with a drastic increase from 2011 to 2015, while the comovement structure of the market changes with different market situations. Most importantly, our study reveals the driving force of causal comovement among individual stocks; that is, sentiment-based factors related to the market index indeed induce excess causal comovement in returns beyond that can be justified by fundamental factors including beta coefficient, book-to-market ratio, liquidity, profitability and volatility. Our study also reveals the determinants of comovement structure, which are attributable to the change of investors' behaviors in different periods. It turns out that investors in the Chinese stock market care about risk-return relationship in normal periods, while they seem to care only about risk in crisis periods.     

Financial development and economic growth nexus: A rejoinder to Tsionas

Tsionas has offered a more revisionist approach to the empirics of the nexus between financial development and economic growth following our paper entitled ‘Financial development and economic growth nexus: A revisionist approach’. In the current note, we engage Tsionas’ approach in tandem with our original finance–growth nexus review. We concur with Tsionas’ approach and reiterate that the debate on the relationship between financial development and economic growth remains a complex terrain both on the theoretical and empirical fronts.     

TACKLING FALSE POSITIVES IN BUSINESS RESEARCH: A STATISTICAL TOOLBOX WITH APPLICATIONS

Serious concerns have been raised that false positive findings are widespread in empirical research in business disciplines. This is largely because researchers almost exclusively adopt the ‘p‐value less than 0.05’ criterion for statistical significance; and they are often not fully aware of large‐sample biases which can potentially mislead their research outcomes. This paper proposes that a statistical toolbox (rather than a single hammer) be used in empirical research, which offers researchers a range of statistical instruments, including a range of alternatives to the p‐value criterion such as the Bayesian methods, optimal significance level, sample size selection, equivalence testing and exploratory data analyses. It is found that the positive results obtained under the p‐value criterion cannot stand, when the toolbox is applied to three notable studies in finance.     

Overnight exchange rate risk based on multi-quantile and joint-shock CAViaR models

Overnight risk of exchange rate is more and more important because the exchange rate trading time of various countries is inconsistent. Drawing on the multi-quantile CAViaR model for two markets, this study proposes a multi-quantile CAViaR model for three markets and a multi-quantile CAViaR model for joint shock. The two new models are used to measure the impact of the U.S. Dollar index and the Euro on the overnight risk for the exchange rate of the Japanese Yen, Hong Kong Dollar, and Chinese Renminbi. The results show that, first, a lag risk affects the overnight risk of the three exchange rates, of which the Renminbi exchange rate is subject to the largest risk. Second, the U.S. Dollar index and Euro exchange rate risks impact the overnight risk of the three exchange rates and this effect is highest for the overnight risk of the Yen's exchange rate. In addition, the impact of the U.S.Dollar index risk is greater than that of the Euro. Third, the Euro and U.S.Dollar index produce a joint shock on the overnight risk of the three exchange rates, and here, the Yen's exchange rate suffers the biggest shock. Finally, the multi-quantile CAViaR model for joint shock is more accurate than that for three markets, particularly when the Hong Kong Dollar exchange rate has a 5% VaR. These empirical results have meaningful implications for regulatory authorities.