Two important dimensions of work related choices are work location and working hours. Telecommuting (working from home or any convenient place instead of commuting to the conventional working place) can potentially have a substantial impact on traffic demand distribution on a particular day by means of its replacement and displacement effect. Consequently, it is of interest to analyze the effect and extent of telecommuting adoption across the labor force. This study proposes a copula based joint discrete multinomial-duration model of choice accommodating the two dimensions of work related choices: work arrangement and aggregated duration of telecommuting episodes on a particular day. In the econometric model telecommuting episodes are defined so as the duration is at least 30 minutes and only home-based telecommuting is considered and sample is drawn from the ATUS, 2007 data. The results from the estimated model show that gender, higher-education, responsibility for child-care, family ties act as driving forces for adopting telecommuting. The sign of the Gaussian copula parameter or dependency parameter implies that the unobserved factors act in opposite direction on the two dimensions: work arrangement choice and aggregated telecommuting episode duration. / text

Duration models are often concerned with time intervals between trades, longer durations indicating a lack of trading activities. In this thesis, we study parameter estimation for the Autoregressive Conditional Duration (ACD) and Stochastic Conditional Duration (SCD) models. Maximum likelihood methods can usually be used in the case of ACD models. However, the SCD models are based on the assumption that durations are generated by a dynamic stochastic latent variable which is often perturbed by Exponential, Weibull, Gamma or Log-Normal distributed innovations. This makes the use of maximum likelihood methods difficult. One alternative method of parameter estimation, in this case, consists in using quasi-maximum likelihood after transforming the original nonlinear model into a state-space model and using the Kalman filter, a similar filtering scheme or the Generalized Method of Moments (GMM). We use the nonlinear filter and GMM method to analyze the Quadratic Stochastic Conditional duration model as well.

Duration models are often concerned with time intervals between trades, longer durations indicating a lack of trading activities. In this thesis, we study parameter estimation for the Autoregressive Conditional Duration (ACD) and Stochastic Conditional Duration (SCD) models. Maximum likelihood methods can usually be used in the case of ACD models. However, the SCD models are based on the assumption that durations are generated by a dynamic stochastic latent variable which is often perturbed by Exponential, Weibull, Gamma or Log-Normal distributed innovations. This makes the use of maximum likelihood methods difficult. One alternative method of parameter estimation, in this case, consists in using quasi-maximum likelihood after transforming the original nonlinear model into a state-space model and using the Kalman filter, a similar filtering scheme or the Generalized Method of Moments (GMM). We use the nonlinear filter and GMM method to analyze the Quadratic Stochastic Conditional duration model as well.

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This paper studies the relationship between individual characteristics of displaced workers and the probability of re-employment. A competing risks hazard model is used, distinguishing between exits from joblessness to self-employment and to paid-employment. All individuals between 25 and 55 years of age, at the time of displacement, that suffered from at least one year of joblessness after being displaced between 1990 and 1998 due to establishment closures that occurred between 1990 and 2001 are included. This allows for the closure procedure to be between one and three years long. Each individual is followed, from the year of displacement until the year of re-employment or at the latest, ten years after displacement. Semi-parametric estimation techniques for discrete time data are used, and in consistency with previous research the results show that subgroups of the jobless individuals experience different re-employment probabilities. The results suggest that a non-immigrant, high income-earner in the mid-thirties, with short tenure at the closing establishment, and who was not displaced early in the closure process and who has lived in the same city for a long time, faces the greatest probability of becoming re-employed. Furthermore, men and individuals with self-employment experience face lower probabilities of re-employment in paid-employments compared to their counterparts. This relationship is however reversed when studying the probability of leaving joblessness for self-employment. Men, immigrants, high income-earners, displaced from smaller establishments, previously self-employed and those with shorter tenure in previous employment are found to be more likely to enter self-employment than their counterparts. A positive duration dependency is prevalent in re-employment probability, suggesting that search activity is increased over time. The probability of self-employment entry is however decreasing the first years of joblessness following displacement, displaying an initial negative duration dependency.

京都大学 / 0048 / 新制・課程博士 / 博士(経済学) / 甲第20870号 / 経博第565号 / 新制||経||283(附属図書館) / 京都大学大学院経済学研究科経済学専攻 / (主査)教授 西山 慶彦, 准教授 山田 憲, 准教授 高野 久紀 / 学位規則第4条第1項該当 / Doctor of Economics / Kyoto University / DGAM

No / The first purpose of this paper is to assess the short-run forecasting capabilities of two competing financial duration models. The forecast performance of the Autoregressive Conditional Multinomial–Autoregressive Conditional Duration (ACM-ACD) model is better than the Asymmetric Autoregressive Conditional Duration (AACD) model. However, the ACM-ACD model is more complex in terms of the computational setting and is more sensitive to starting values. The second purpose is to examine the effects of market microstructure on the forecasting performance of the two models. The results indicate that the forecast performance of the models generally decreases as the liquidity of the stock increases, with the exception of the most liquid stocks. Furthermore, a simple filter of the raw data improves the performance of both models. Finally, the results suggest that both models capture the characteristics of the micro data very well with a minimum sample length of 20 days.

Background: The volatility in the interest rate market have increased during the last decade and this have made interest rate risk management more important for  both financial institutions and non-financial companies with short- and long term financial commitments. Objective: The main objective of this thesis is to analyze different ways of measuring interest rate risk in the treasury operations an international industrial company group. Further, the study will also examine the way treasury departments of international industrial company group’s measure interest rate risk and explain why this method have been chosen. Method: The research method of the thesis is a case study and a mix of both quantitative and qualitative data has been used to conduct it. The quantitative data have been secondary data received from TIFI’s treasury management software and the qualitative data have been collected through a survey with eight treasury managers from other international industrial company groups. Conclusion: The repricing model is suitable because it is straight forward, fairly easy to communicate to management and it focuses on the book value. However, defining relevant time buckets might be difficult. The duration model is a good measurement tool because it can be used in a variety of ways, but a disadvantage is that it focuses on the market value, which might not be appropriate for treasury departments. Stress testing captures the true change in market value, but demands forecasts about future interest rate movements and lacks tools to manage the interest rate risk. Treasury departments of international industrial company groups use a variety of measurement methods. The most frequently used methods are duration-, maturity- and Value at Risk models and different kinds of stress tests. The method should not only measure the interest rate risk in a correct way but it should also be easily explained to management and other executives in the company that might not have knowledge about financial economics. The main difference between treasury departments and commercial banks is that commercial banks try to earn money on interest rate fluctuations, whereas treasury departments want to minimize the impact of interest rate fluctuations in order to support the company group’s core business.

This thesis consists of four essays, mainly related to the fields of industrial organization and political economy. The focus is on deregulation of electricity retail markets and on the continued regulation of parts of such markets after the introduction of competition. The first essay is an empirical essay on the causes of deregulation. The timing of implementation of competition in retail electricity markets in the United States, Canada, Europe, Australia and New Zealand is studied. One conclusion is that there exist important qualitative differences between the United States and Europe. While deregulation in the United States to a large extent seems to have been driven by consumer interest concerns, the influence from interest groups is more pronounced in Europe.The second (theoretical) and third (empirical) essays deal with the interaction between the regulation of distribution networks and the retail market. When the regulated and unregulated operations are conducted within vertically integrated companies the regulation may not only have an effect on the regulated market, but also affect the behavior in the unregulated market. In the third essay a test that uses prices to detect patterns of cross-subsidization is developed and used on Norwegian data. Especially the effects of a regulatory change on cross-subsidization behavior are analyzed. The results both highlight the importance of a well-designed regulation of the regulated market and give support to requirements of vertical separation between regulated and unregulated operations.The fourth essay is a study of domestic electricity demand. It is thus somewhat different than the other papers since it is not directly connected to the issue of electricity market deregulation. Since the energy sector is an essential part of any modern economy and energy production has considerable environmental effects, the sector has for a long time been subject to political interventions. To some extent the policy instruments available to the legislator are reduced by deregulations. The use of taxes to affect prices and thus the demand for electricity may at the same time become an even more important policy instrument and more difficult to implement due to the internationalization of the electricity market. / Diss. Stockholm : Handelshögsk., 2003

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