The impact of corporate strategy on the capital structure of Australian companies

Research into the capital structure of firms has been the subject of extensive empirical investigation but further progress may be constrained by the conventional paradigm underlying most of this work. This paper seeks to extend the debate by examining the endogenous influence of corporate strategy on financing decisions made by firms. While the theoretical specification of the possible relationship has to be developed further, various models were constructed and company data from Australia, an economy with some notoriety for fairly loose corporate debt management, was used to examine various hypothesized relationships. Our analysis suggests that corporate strategy influences capital structure, particularly for the most diversified firms, and that the emerging relationship is complex. Profit, cash flow, the rate of growth and the level of earnings risk are important additional internal influences on capital structure. The results are reasonably robust and indicate that this focus of enquiry has considerable potential for further resolution of the capital structure puzzle, as well as contributing to the debate on the impact of institutional shareholders on the corporate strategy of the firms in which they invest.     

Testing for unit roots in time series models with non-stationary volatility

Many of the key macro-economic and financial variables in developed economies are characterized by permanent volatility shifts. It is known that conventional unit root tests are potentially unreliable in the presence of such behaviour, depending on a particular function (the variance profile) of the underlying volatility process. Somewhat surprisingly then, very little work has been undertaken to develop unit root tests which are robust to the presence of permanent volatility shifts. In this paper we fill this gap in the literature by proposing tests which are valid in the presence of a quite general class of permanent variance changes which includes single and multiple (abrupt and smooth-transition) volatility change processes as special cases. Our solution uses numerical methods to simulate the asymptotic null distribution of the statistics based on a consistent estimate of the variance profile which we also develop. The practitioner is not required to specify a parametric model for volatility. An empirical illustration using producer price inflation series from the Stock–Watson database is reported.     

THE RELATIONSHIP BETWEEN THE BLACK MARKET AND OFFICIAL EXCHANGE RATES: AN EXAMINATION OF LONG-RUN DYNAMICS IN INDIA

This study is the first to use Johansen's cointegration approach for India in the analysis of the long‐term dynamics between the black and official exchange rates for the period 1953–1993. The study also estimates the long‐run elasticity of the official rate with respect to the black market rate. As monthly data over 40 years are used, and a more robust methodology is employed, the results are likely to be more reliable as compared with the earlier work on India. The results of our study suggest that while there is a long‐term relationship between the two rates, the direction of causality is from the black rate to the official exchange rate. This is plausible in the Indian context where policy has generally lagged behind events in the black market. The hypothesis of a constant black market premium is rejected, implying that there is a mismatch between the percentage change in the official exchange rate and the percentage change in the black market rate.     

Learning by doing,spillovers and shakeouts

This paper studies industry evolution driven by non strategic learning by doing and spillovers. We characterize a dynamic process of cost and output changes and its effect on welfare and industry profits. The paper gives conditions for shakeouts to occur and analyzes the key factors affecting these conditions. Since shakeouts could lead to a long-run social loss due to higher market concentration, there is a role for a government to play in limiting unnecessary shakeouts. The most effective way to do so is to enhance spillovers.JEL Classification: L11, L13, O31Correspondence to: Michael TroegeWe would like to thank Hans Mewis, Christophe Moussu and an anonymous referee for valuable comments and suggestions. We also benefited from comments of seminar participants at WZB, Humboldt University, Northwestern University and the EEA/ESEM 1999 meetings. Part of the research was carried out while Michael Tröge was visiting Northwestern University. Financial support by the German Research Council (DFG) is gratefully acknowledged.     

Timing of Public Information and Cost Reduction

Received July 31, 2000; revised version received July 18, 2001     

Comprehensive assessment of patients with irritable bowel syndrome with constipation and chronic idiopathic constipation using deterministically linked administrative claims and patient-reported data: the Chronic Constipation and IBS-C Treatment and Outcomes Real-World Research Platform (CONTOR)

Abstract

Aims

To characterize a US population of patients with irritable bowel syndrome with constipation (IBS-C) or chronic idiopathic constipation (CIC) using CONTOR, a real-world longitudinal research platform that deterministically linked administrative claims data with patient-reported outcomes data among patients with these conditions.     

Sample attrition and labor force dynamics: Evidence from the Spanish labor force survey

In this paper we examine a number of issues that arise in investigating labor force dynamics using the Spanish Labor Force Survey (EPA). These issues are by no means specific to the Spanish case and apply to most European-style labor force surveys. Our main conclusions may be summarized as follows. First, survey nonresponse cannot be neglected. Second, the EPA tends to underestimate employment and participation of high-educated young people, and to overestimate those of the low-educated elderly. Finally, we find little evidence that attrition causes important selection biases in estimating quarterly transition probabilities.