Due to social norms, corporate timing, and all kinds of psychological behavior patterns, microeconometric data is likely to be cross-sectionally (or “spatially”) dependent. This potential dependence constitutes a challenge for the analysis of panel data on the firm or private investor level, as it is well known that erroneously ignoring spatial correlation can lead to severely biased statistical results. Empirical scientists have therefore devoted great efforts in developing methodologies which ensure that statistical inference is valid even in the presence of cross-sectional dependence. One of the most popular techniques that has emanated from this research is the calendar time portfolio approach (or the Jensen alpha approach) whose origin goes back to the work of Jaffe (1974) and Mandelker (1974). The calendar time portfolio approach (subsequently abbreviated as the CalTime approach) as it is employed in recent studies constitutes a two-step procedure. Thereby, the first step involves computing an average return for the cross- section of investors or firms, and the second step then measures the risk-adjusted performance by estimating a multifactor (e.g. the Fama-French three factor) time-series regression model.
In this paper, we present a regression-based generalization of the CalTime approach. Our methodology relies on estimating, either on the investor or firm level, a linear regression model with Driscoll and Kraay (1998) standard errors. We show both theoretically and empirically, that this “GCT-regression model” is capable to replicate the results of the traditional calendar time portfolio approach in a single step rather than in two. Since Driscoll-Kraay standard errors are spatial correlation consistent, our methodology further confirms the findings of Lyon, Barber, and Tsai (1999, p. 193) who report that the calendar time portfolio approach “eliminates the problem of cross sectional dependence among sample firms because the returns on sample firms are aggregated into a single portfolio”.
Proper vehicle maintenance not only helps to keep your vehicle in good working condition, but also helps the environment. All recommended maintenance is important. Improper vehicle maintenance can even affect the quality of the air we breathe. Improper fluid levels or the wrong tire inflation can increase the level of emissions from your vehicle. To help protect our environment, and to keep your vehicle in good condition, be sure to maintain your vehicle properly.
When the CHANGE OIL SOON message in the Driver Information Center (DIC) comes on, it means that service is required for your vehicle. See DIC Warnings and Messages on page 3-40. Have your vehicle serviced as soon as possible within the next 600 miles (1 000 km). It is possible that, if you are driving under the best conditions, the engine oil life system may not indicate that vehicle service is necessary for over a year. However, your engine oil and filter must be changed at least once a year and at this time the system must be reset. Your GM Goodwrench® dealer has GM-trained service technicians who will perform this work using genuine GM parts and reset the system. If the engine oil life system is ever reset accidentally, you must service your vehicle within 3,000 miles (5 000 km) since your last service. Remember to reset the oil life system whenever the oil is changed. See Engine Oil Life System on page 5-20 for information on the Engine Oil Life System and resetting the system.
You’ve spent time building the framework and operations behind your business. Now it’s time to explore the different aspects of business insurance coverage and gain a deeper understanding of how it protects your assets and investments.
In this guide, you’ll learn how business insurance coverage works for you, the different types of business insurance coverage and protection available, as well as business insurance terms, so you can choose the right type and policy for your company.
