Competition and efficiency in the MENA banking region: a non-structural DEA approach

The goal of this article is to empirically assess the relationship between competition and efficiency in the banking sector of Middle East and North African (MENA) countries spanning the period 1997–2011. To measure the level of competition, the article estimates the non-structural indicator known as the H-statistic, while the level of bank efficiency is estimated through the nonparametric methodology of the Data Envelopment Analysis (DEA) and the Bootstrap Data Envelopment Analysis (BDEA), respectively. The empirical results are robust under six econometric methodologies, providing sufficient evidence for the presence of a one-way (negative) Granger causality, running from efficiency to competition. The empirical findings lead to the rejection of the ‘Efficient Structure Hypothesis’, implying that increases in competition do not precede increases in cost efficiency.     

Financial Market Data Versus Accounting Data: Which Better Explains Stock Returns?

This paper presents the comparison of how financial market and accounting data affect stock prices and returns. The goal was to ascertain whether financial information or accounting data dominate in evaluating stock prices. Most valuation techniques used by firms are based on models using either accounting variables (earnings, book value, cash flows, research and development expenses) or financial market data (e.g. beta, market value, interest). The answer is of great importance for valuators and investors as it will help them focus on the most important variables and make better valuations and choices. This answer is also important for accounting standard setters as the preferred method will serve as an indicator for the quality of financial statements and their importance to users. The paper contributes to the existing literature in the fields of value relevance of accounting information and firm valuation and accounting standards (e.g. International Financial Reporting Standards, United States General Accepted Accounting Principles). To answer this question, share prices were estimated based on financial data using the capital asset pricing model and for accounting data, using Ohlson’s model. The results were tested for both methodologies by comparing estimated share prices with actual ones. The greater the correlation between the two variables the better the explanatory power of the model. The focus was on S&P 500 firms for the period 2002–2017.

     

Modeling the time varying volatility of housing returns: Further evidence from the U.S. metropolitan condominium markets

This study extends the literature on modeling the volatility of housing returns to the case of condominium returns for five major U.S. metropolitan areas (Boston, Chicago, Los Angeles, New York, and San Francisco). Through the estimation of ARMA models for the respective condominium returns, we find volatility clustering of the residuals. The results from an ARMA‐TGARCH‐M model reveal the absence of asymmetry in the conditional variance. Dummy variables associated with the housing market collapse unique to each metropolitan area were statistically insignificant in the conditional variance equation, but negative and statistically significant in the mean equation. Condominium markets in Los Angeles and San Francisco exhibit the greatest persistence to volatility shocks.     

Being Innovative While Being Green: An Experimental Inquiry into How Consumers Respond to Eco‐Innovative Product Designs

Eco‐innovations are an effective way for companies to strategically align themselves with customers’ growing environmental concerns. Despite their crucial role, scant research has focused on eco‐innovative product designs. Drawing from the sustainability and innovation literature, this article proposes that in the design of an eco‐innovation, its degree of innovativeness, level of eco‐friendliness, and detachability significantly affect consumers' adoption intentions. This article develops various conceptual models tested through three independent online experiments with U.S. consumers. The findings support the hypotheses and provide useful insights into the underlying mechanisms of how and why consumers respond to eco‐innovative product designs across various high‐tech product categories. Specifically, the results show (1) a positive effect of innovativeness degrees of eco‐innovative attributes on consumers' perceptions of product eco‐friendliness and on their adoption intentions as well as a significant moderating role of consumers' need for cognition (Study 1); (2) a positive influence of eco‐friendliness levels of eco‐innovative attributes on consumer adoption intentions in the case of high‐complexity products but not for low‐complexity products, emphasizing the need to adopt different approaches when developing eco‐innovations to ensure favorable consumer reactions (Study 2); and (3) a significant impact of the detachability of eco‐innovative attributes on consumers' perceptions of trade‐offs between environmental benefits and product functionality and on their intentions to adopt eco‐innovations (Study 3). These findings add to existing theoretical knowledge, provide actionable managerial implications, and identify fruitful avenues for future research.     

Resurrecting the size effect: Evidence from a panel nonlinear cointegration model for the G7 stock markets

Firm size is known to be an important factor affecting stock returns. This study proposes a panel threshold cointegration model to investigate the impact of the size effect on stock returns for the panel of G7 countries: Canada, France, Germany, Italy, Japan, the U.K., and the U.S. over the period 1991:1–2012:12. The empirical analysis is based upon the nonlinear cointegration framework using the asymmetric ARDL cointegration methodology (Shin et al., 2011). This methodological approach permits a much richer degree of flexibility in the dynamic adjustment process toward equilibrium, than in the classical linear model. Our findings indicate the presence of asymmetric adjustment around a unique long-run equilibrium. In particular, the empirical analysis provides evidence of asymmetric effects between stock returns and the size effect, while controlling for the book-to-market ratio and the price-to-earnings ratio.     

Reducing High Public Debt Ratios: Lessons from UK Experience*

This paper examines contrasting experiences of the United Kingdom in addressing high public debt to GDP ratios following major wars. A clear message is that interest rate / growth rate differentials were more important than primary budget surpluses for the different outcomes. The debt to GDP ratio fell very rapidly under financial repression following the Second World War but remained stubbornly high despite large budget surpluses with price deflation after the First World War. Implications for policymakers today are that averting price deflation is a high priority and that supply‐side policies that raise growth could play an important part in debt reduction.     

Default estimation,correlated defaults,and expert information

Capital allocation decisions are made on the basis of an assessment of creditworthiness. Default is a rare event for most segments of a bank's portfolio and data information can be minimal. Inference about default rates is essential for efficient capital allocation, for risk management and for compliance with the requirements of the Basel II rules on capital standards for banks. Expert information is crucial in inference about defaults. A Bayesian approach is proposed and illustrated using prior distributions assessed from industry experts. A maximum entropy approach is used to represent expert information. The binomial model, most common in applications, is extended to allow correlated defaults yet remain consistent with Basel II. The application shows that probabilistic information can be elicited from experts and econometric methods can be useful even when data information is sparse. Copyright © 2009 John Wiley & Sons, Ltd.