Introduction

1.1 Set the scene

Companies in the oil industry are allowed to choose between two accounting methods for the exploration and development cost of oil wells, successful efforts and full cost. Although there are some minor differences, the major difference in these methods is how they account for dry wells drilled. Under full cost accounting, a company capitalizes the relevant costs related to wells and depreciates these assets over time, regardless of whether oil is found or not. Under successful efforts accounting, only wells where oil is found gets capitalized and depreciated over time, investments in empty wells are regarded as costs. For successful efforts companies there are firm specific choices, as in when they confirm that they will not produce from an oil well etc., but overall, companies with full cost will have a higher balance and lower expenses due to capitalizing the expenses of empty wells as an asset, not treating it as a a cost.

This directly influences the bottom line of financial reports. Successful efforts companies will incur the costs earlier and have lower assets than full cost companies. Consequently full cost companies look more favorable to investors (Baker 1976). This is used as an argument for why companies should be allowed to use it, as it encourages investments into oil companies.

Successful efforts accounting is considered to give a more accurate representation of the firm (Baker 1976).

In this thesis I will not focus on which method should be used, but rather if there are any unwanted effects from having both methods be legal. By analyzing the earnings response coefficient and the value relevance, I seek to contribute to the existing knowledge on valuation of full cost- and successful efforts firms.

1.2 Motivation

There are several research reports that focus on comparing the differences between successful efforts and full cost in value relevance and earnings response coefficient analysis. However, these focus less on the implications and long-term effect of these differences. In addition, previous studies do not included lagged variables, nor how earlier years drilling success might impact the current year. I discuss this in chapter two.

This study replicate the methodology from previous research on earnings response coefficient

(Teoh and Wong 1993) and value relevance (Misund, Osmundsen, and Sikveland 2015), and

conduct the analysis on a more recent dataset. The thesis expands upon this research by

adding new variables. This include drilling success and number of net wells drilled. By adding these variables the study enables a more detailed analysis of differences between full cost and successful efforts companies, and provides a deeper understanding of how the different type of accounting affects investor’s opinions of the companies. I find it highly motivating to put a new spin on the existing literature, and include new variables that have yet to be analyzed.

1.3 Problem Statement

The main purpose of this thesis is to create deeper insight into the effects from having both successful efforts and full cost accounting. In order to fit this purpose into a statement that can be applied for both my value relevance and earnings response coefficient analysis, I have chosen to answer a fairly general problem statement.

"How does full cost and successful efforts accounting affect the link between book values and market values?”

In order to answer this overarching statement and to structure the thesis, I will provide answers to the following sub-questions.

• Does oil price behavior affect value relevance and earnings response coefficients analysis?

• How does drilling success affect the accuracy of current and future value relevance and earnings response coefficients analysis?

• Is oil price change an important variable in value relevance and earnings response coefficients analysis?

• Are value relevance and earnings response coefficients analysis comparable?

1.4 Delimitations

During the process of my master thesis it has been necessary to make several delimitations in order to focus on the primary issues and make the process manageable. In order to present reliable, robust and relevant results I have taken the following delimitations.

• The datasets used for earnings response coefficient and value relevance analysis are

different, due to lack of data in some observations and the earnings response

coefficient only consists of firms traded as of year end 2015, and the value relevance

analysis consists of all firms where that has reported sufficient data for one or more years between 1991 and 2015.

• The datasets have been edited; I have removed the 0.5% highest and lowest observations in both analyses. This is to remove any problems caused by outliers (Zimmerman 1994; 1995; 1998).

• No weighting is used, to simplify the thesis I have not weighted any variables, regardless of them benefiting from weighting. This means some of the findings might be less significant then what optimized variables would find.

• Data inconsistencies, I have found some faults in the data from Reuters, I cannot be absolutely sure that I have found and corrected all the faults.

Because of data inconsistencies, I have only used traded firms in my earnings response coefficient analysis. The reason for not including firms that are no longer traded in the earnings response coefficient analysis is because the data from these companies is poor. In short, finding the correct trading data from firms going through bankruptcy, mergers and acquisitions proved difficult. This is because firms continued on the same ticker after mergers

& acquisitions, making it hard to know if the ticker is correct, or if it is the relevant information form the balance sheet information gathered from IHS Markets. I also experienced several problems with errors in Reuter’s data from old firms. Faults such as the annual report date being set to the 31.12, instead of the day the report was actually publicized, was common. This problem is not present in the value relevance analysis because I am only using IHS Market data in the value relevance analysis.

1.5 Structure of the Thesis

The rest of this paper is organized as follows: In chapter two I give a brief overview of the

background and previous research. In chapter three I give a quick overview of the more

advanced methodology used to create robust results. In chapter four I present the earnings

response coefficient analysis and findings, this includes methodology; data, analysis and

discussions related to my earnings response coefficient findings. In chapter five I do the same

for the value relevance analysis; here I present methodology, data, analysis and discussions

related to my value relevance findings. Following this in chapter seven I present a summary

discussion and conclusion of what the findings indicate. Finally in chapter eight I give my

recommendations for further research.