Mohammed Khaled

Parametric Productivity Measurement and Choice among Flexible Functional Forms

This paper formulates and estimates a model of producer behavior for U.S. manufacturing 1947-71 that simultaneously identifies substitution elasticities, scale economies, and the rate and bias of technical change. A nonhomothetic, nonneutral generalized Box-Cox cost function is employed which takes on the generalized Leontief, generalized square-root quadratic, and translog cost functions as special or limiting cases. Total factor productivity is estimated parametrically rather than being computed as the residual of growth in outputs minus growth in inputs. We find substantial economies of scale and relatively little technological change.

Calendar anomalies in REITs: international evidence

Purpose – The purpose of this paper is to determine the relative magnitude of calendar anomalies in international Real Estate Investment Trusts (REITs). The anomalies are the prior day effect, the Monday effect, the turn‐of‐the‐month effect and the January effect. The results are based on 14 countries. The corresponding stock index is used as the reference by which to gauge the anomalous behaviour of each REIT.Design/methodology/approach – There are two primary dimensions to the statistical design. Between‐country differences, based on Gross Domestic Product (GDP) and a measure of shareholder protection, are examined using a panel model. Differences between the REITs and their stock index are examined using a repeated measures dependent variable design.Findings – The presence of the four calendar anomalies is apparent in the REITs and the stock indices. There is not sufficient evidence to show that the magnitudes of the Monday, the turn‐of‐the‐month and the January anomalies differ between REITs and stock...

A note on the turn of the month and year effects in international stock returns

This examination of the turn of the month (TOM) and turn of the year (TOY) effects in 50 international stock indices, for the period 1994–2006, characterises the degree that the effects are influenced by: (i) the gross domestic product of the economy, (ii) the sign of the return on the prior day (called the prior day effect), (iii) a temporal indicator and (iv) the Monday effect. These effects are assessed by the use of an estimated generalised least squares (EGLS) panel regression model incorporating panel-corrected standard errors. Three important results relating to the TOM and TOY effects are observed. When the prior day effect on control days is used as the reference and controls are made for market development and year, we find that: (i) there is a relatively enhanced return on all TOM days, (ii) there is a relatively enhanced return on good TOY days and (iii) returns of bad TOY days are not remarkable.

New Zealand's love affair with houses and cars

Rapidly rising house prices over the last few years has drawn the attention of researchers to the drivers lying behind both supply and demand side influences in the housing market. This study complements much of that work by attempting to uncover the price and income parameters for rental and owner‐occupied housing in New Zealand in relation to all other goods and services purchased by households. The research quantifies a point long understood informally about demand behaviour in this country, that the demand for housing (and cars) is particularly income elastic. This has important implications for policy makers who attempt to constrain speculative housing demand. Another notable feature of the period has been an apparent trend away from owner occupied housing towards rental accommodation. The research is carried out using Household Economic Survey data through 2004.

Yet another careful re-examination of the SAD hypothesis

Purpose - – The focus is on the seasonal affective disorder SAD hypothesis of Kamstra, Kramer and Levi (KKL). Examines the arguments advanced by KKL (2012) in their reply to the criticisms of the hypothesis raised by Kelly and Meschke (2010). Design/methodology/approach - – Uses a mixture of research synthesis and standard statistical analysis to investigate the reliability of the claims raised and the veracity of the statistical arguments. Findings - – The synthesis of the literature, and of the empirical models employed therein, raises questions about the validity of the SAD hypothesis. Originality/value - – Offers a rigorous analysis of whether there is a sound statistical basis for the SAD hypothesis which is frequently cited in the literature as support for the importance of behavioural finance.

Why you should use high frequency data to test the impact of exchange rate on trade

This study suggests that testing the impact of exchange rate on trade should be done using high frequency data. Using different data frequencies for identical periods and specifications between the US and Canada, we show that low frequency data might suppress and distort the evidence of the impact of exchange rate on trade in the short-run and the long-run.

Rugby Results and Investor Sentiment in New Zealand

This paper contributes to the existing literature on sports-related market anomalies by examining whether losses by the New Zealand national rugby team (the All Blacks) affect stock market returns in New Zealand. The novelty of this paper is in its use of a probability model to control for the ex-ante probability of a win in regression analysis, so that the economic effects of a rugby loss can separated from its cognitive effects on investors’ behaviour. The paper finds support for statistically significant effect of the probability of an All Blacks win, but, initially, not for the cognitive effect of an All Blacks loss on New Zealand stock market returns. Further robustness tests, which correct for heteroskedasticity, use different modelled probabilities and treat the effect of a draw as the same as that of a loss similarly fail to reject the hypothesis that an All Blacks loss has no effect on the investors’ trading behaviour. However, consistent with the small firm anomalies in general, tests using the small cap index offer some support.

Estimating Bias of Technical Progress with a Small Data Set

Economic historians frequently face the challenge of estimation and inference when only a small sample of the relevant data is available. We illustrate solutions to the challenges through a case study analysis of the Uselding and Juba (1973) data. They have only seven observations available to estimate of the bias of technical progress in United States manufacturing in the nineteenth century. They are able to offer estimates of the bias only by assuming that production technology is not Cobb-Douglas, technical progress is non-neutral and that elasticity of substitution between labour and capital is less than 0.9. These assumptions could not be tested owing to the paucity of the required historical data. This case study illustrates the use of both additional theoretical information and appropriate statistical techniques to alleviate problems of estimation and inference with small samples.

Seasonal Affective Disorder and IPO Underpricing: Updated Evidence

Using several proxies for seasonal affective disorder (SAD), we find that SAD negatively affects IPO first trading day return (underpricing) during the 1981-1989 and 1999-2000 periods, but not during the 1990-1998 and 2001-2007 periods. During those periods when SAD affects IPO underpricing, firm exposure mitigates the negative effect of SAD. In addition, over the years 1981-2000, we find a negative effect of SAD on the offer price revision of the IPO during bookbuilding, which suggests pre-market investors adjust for SAD effects during the bookbuilding process.

The Seasonal Affective Disorder: The Seasons versus the Length of Night

Kamstra et al. (2003, 2011) offer measures of the prevalence of the seasonal affective disorder based on the hours of night and the medical incidence of the disorder in the North American population. Simpler measures are constructed by Kliger et al. (2012) using variables based upon the four seasons. Applying correlation analysis and factor analysis, we find these two sets of measures are empirical substitutes. We suggest researchers use the simpler seasonal mood variables of Kliger et al. rather than the more complicated measures of Kamstra et al. when examining the influence of the seasonal affective disorder on asset prices.