Effects of limit order book information level on market stability metrics

Using an agent-based model of the limit order book, we explore how the levels of information available to participants, exchanges, and regulators can be used to improve our understanding of the stability and resiliency of a market. Ultimately, we want to know if electronic market data contains previously undetected information that could allow us to better assess market stability. Using data produced in the controlled environment of an agent-based model’s limit order book, we examine various resiliency indicators to determine their predictive capabilities. Most of the types of data created have traditionally been available either publicly or on a restricted basis to regulators and exchanges, but other types have never been collected. We confirmed our findings using actual order flow data with user identifications included from the CME (Chicago Mercantile Exchange) and New York Mercantile Exchange. Our findings strongly suggest that high-fidelity microstructure data in combination with price data can be used to define stability indicators capable of reliably signaling a high likelihood for an imminent flash crash event about one minute before it occurs.     

Franchisee leadership traits vs. manager leadership traits an exploratory study comparing hope, leadership, commitment and service quality delivery

In order to add to the understanding of the role of franchising in entrepreneurship and to help franchise systems improve efficiency, the constructs of organizational leadership, hope, organizational commitment, and service quality perceptions of franchised managers and franchisees are differentiated in the current study. For scholars and practitioners, the dynamic relationship between entrepreneurship, franchisees, and management is an important triangle which merits further investigation. While the results offered only that managers and franchisees differed statistically in service empathy, differences were noted across all areas which approached significance but was limited due to the small sample size. Implications for future research are discussed.     

OVERBIDDING AND HETEROGENEOUS BEHAVIOR IN CONTEST EXPERIMENTS: A COMMENT ON THE ENDOWMENT EFFECT

We revisit the meta-analysis of Sheremeta on overbidding in contest experiments and focus on the effect of endowment on overbidding. Sheremeta assumes, and finds evidence of, an increasing linear relationship between endowment and overbidding, Quantal Response Equilibrium (QRE) predicts an increasing concave relationship, while Baik and colleagues find an inverted U-shaped relationship in their analysis of a single experiment. We use the same data as in Sheremeta, but employ a different econometric model which leads to support for both QRE and the inverted U-shaped relationship. Following Baik and colleagues, we posit that the inverted-U relationship may be interpreted in terms of a wealth effect.     

Transport subsidies, system choice, and urban sprawl

This paper analyzes the effect of transport subsidies on the spatial expansion of cities, asking whether such subsidies are a source of undesirable urban sprawl. Even though the cost-reducing effect of transport subsidies is offset by a higher general tax burden (which reduces the demand for space), the analysis shows that subsidies nevertheless lead to spatial expansion of cities. If the transport system exhibits constant returns to scale, the subsidies are inefficient, making the urban expansion they entail undesirable. The paper also studies transport “system choice,” with the city portrayed as selecting its transport system from along a continuum of money cost/time cost choices. The analysis shows that subsidies inefficiently bias choice in the direction of a high money cost/low time cost option. Lastly, the paper considers system choice in a city with rich and poor groups, showing that the rich favor a system with a high money cost and low time cost, but that their choice, if implemented, leads to a city whose spatial size is smaller than optimal. Thus, rich control of system choice does not lead to urban sprawl.     

Diagnosing housing fever with an econometric thermometer

Housing fever is a popular term to describe an overheated housing market or housing price bubble. Like other financial asset bubbles, housing fever can inflict harm on the real economy, as indeed the U.S. housing bubble did in the period following 2006 leading up to the general financial crisis and great recession. One contribution that econometricians can make to minimize the harm created by a housing bubble is to provide a quantitative “thermometer” for diagnosing ongoing housing fever. Early diagnosis can enable prompt and effective policy action that reduces long-term damage to the real economy. This paper provides a selective review of the relevant literature on econometric methods for identifying housing bubbles together with some new methods of research and an empirical application. We first present a technical definition of a housing bubble that facilitates empirical work and discuss significant difficulties encountered in practical work and the solutions that have been proposed in the past literature. A major challenge in all econometric identification procedures is to assess prices in relation to fundamentals, which requires measurement of fundamentals. One solution to address this challenge is to estimate the fundamental component from an underlying structural relationship involving measurable variables. A second aim of the paper is to improve the estimation accuracy of fundamentals by means of an easy-to-implement reduced-form approach. Since many of the relevant variables that determine fundamentals are nonstationary and interdependent we use the endogenous instrumental variable based method (IVX) to estimate the reduced-form model to reduce the finite sample bias which arises from highly persistent regressors and endogeneity. The recursive evolving test proposed by Phillips, Shi, and Yu (PSY) is applied to the estimated nonfundamental component for the identification of speculative bubbles. The new bubble test developed here is referred to as PSY-IVX. An empirical application to the eight Australian capital city housing markets over the period 1999–2017 shows that bubble testing results are sensitive to different ways of controlling for fundamentals and highlights the importance of accurate estimation of these housing market fundamentals.     

Instrumental variable estimation based on grouped data

The paper considers the estimation of the coefficients of a single equation in the presence of dummy intruments. We derive pseudo ML and GMM estimators based on moment restrictions induced either by the structural form or by the reduced form of the model. The performance of the estimators is evaluated for the non-Gaussian case. We allow for heteroscedasticity. The asymptotic distributions are based on parameter sequences where the number of instruments increases at the same rate as the sample size. Relaxing the usual Gaussian assumption is shown to affect the normal asymptotic distributions. As a result also recently suggested new specification tests for the validity of instruments depend on Gaussianity. Monte Carlo simulations confirm the accuracy of the asymptotic approach.     

The Last Word on the Wage Curve?

Abstract.  Since 1990, there has been extensive international research on the responsiveness of wages of individuals to changing local labour market conditions. For many countries, an inverse relationship between wages and local unemployment rates has been found. In their book, The Wage Curve , Blanchflower and Oswald argued that the unemployment elasticity of pay is around −0.1 in most countries. In a 1995 literature survey, Card referred to this striking empirical regularity as being close to an 'empirical law of economics'. Nonetheless, reported elasticities do vary, even excluding outliers, between about −0.5 and +0.1. There is also considerable heterogeneity among wage curve studies in terms of data and model specification. This paper carries out meta‐analytic techniques on a sample of 208 elasticities derived from the literature to uncover the reasons for the differences in empirical results across studies. Several causes of variation are identified. There is also clear evidence of downward publication bias. In addition, many reported t ‐statistics are biased upwards due to the use of aggregate unemployment rates. A maximum likelihood method and a trimming procedure are used to correct for these biases. Both methods give similar results for our sample. An unbiased estimate of the wage curve elasticity at the means of study characteristics is about −0.07.     

An Integrative Framework for Measuring the Extent to which Organizational Variables Influence the Success of Process Improvement Programmes

abstract    Studies on the three types of process improvement programmes (Continuous Improvement, Reengineering and Benchmarking) have appeared many times in the literature. These studies suggest that certain organizational variables act as enablers and their presence or absence can significantly influence success rates. Such studies have tended to examine companies where a single programme has been implemented. In contrast, this paper examines a sample of companies who have experienced all three programmes. Our aim is to compare and contrast each programme's impact on firm performance and identify which organizational variables are common and which are programme-specific enablers of success. We build and test an integrative framework to support our analysis. Our study found that: (1) Reengineering delivered the greatest impact on performance; (2) executive commitment was needed to make this happen; (3) strategic alignment was the major influence on the success rate of Reengineering and Continuous Improvement programmes; and (4) employee empowerment was necessary for each programme to work effectively.