How to write a Master thesis
Lennart Hjalmarsson Centre For Finance - CFF Göteborg School of Business, Economics and Law PO Box 640, S-40530 Göteborg 1 Version: 18th of Novermber, 2005 1. INTRODUCTION The purpose of this paper is to give some advice to students writing their Master thesis. Typically students spend too much time in trying to …nd an interesting topic for a thesis. The student counsellor has a set of topics that will attract the interest of potential supervisors. Many companies also have an inventory of problems that they are interested in. This can be a good …rst contact with a potential employer. However, DO NOT CONTACT companies unless they have voluntarily stated that it is OK after your …rst e-mail contact. Selecting a topic for a thesis is therefore normally not a problem, all topics are interesting if treated with imagination and based on detailed knowledge. The probability of success is therefore more dependent on the use of concepts that the student has internalised rather than some new technique. The best way of getting an idea about the ideal "look and feel" for your thesis, is to read several articles in recognised journals. However, remember that the target audience of these articles is the professional research community in a speci…c …eld. Whereas, your audience is your fellow students. This di¤erence will therefore de…ne which concepts that you will have to clarify and typically add to the length of the paper. Methods or ideas covered in mandatory courses, eg. CAPM or standard econometric techniques should not be explained. 2. PLAN Familiarise yourself with the present research by reading a good survey article that is focused on your topic. Prior to starting with the thesis, you should provide the student counsellor with a structured plan (max. 2 pages) for your thesis. This should contain: What is the problem that you want to address and why is this important? What kind of results do you expect to …nd? What Sections do you want to include and what kind of questions do you want to answer in each Section? If the paper is empirical, how do you …nd data? Are you sure that this data is available to you,
This guideline is to a large extent based on my seminar series to future PhD students titled - "How to write a paper". The usual disclaimer applies. 1 e-mail address:lennart.hjalmarsson@economics.gu.se; tel:+46 31 773 1345.
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what kind of software packages are needed and do you have a working knowledge of them? Do you have a suggestion for a supervisor? The plan should be …nalised and approved three months prior to when you expect to start with the work. We strongly suggest that you co-write your thesis with a fellow student. When making the choice of co-author, try to …nd someone with similar rather than complementary competencies to yourself. If for some reason, your colleague decides to abandon the project, you will be in a much better position to …nalise the paper. Having similar interests will also make it easier to adhere to the original plan. One month after you have started your work, you should present your mid-thesis report (max. 10 pages), which will be commented upon by a fellow student. The …nal report should be presented no later than 10 weeks after you started. After this, only minor adjustments should be made. To be able to …nish a project according to the original time plan is of outmost importance. 3. LAYOUT AND STYLE Do not spend too much time on this issue until the …nal stage. Successive changes will make some of your intermediate work obsolete. However, writing becomes much simpler if you use automated references to Equations, Sections, Figures and Tables as well as to citations. Keep each object (Figure and / or Table) centred on a single page and after the Section - References. Make sure that objects are self-explanatory. Put markers in the text where you want the object to be inserted. Use a style that is generally accepted, cf. the style guide of Journal of Finance, which is available on the American Finance Association homepage. To facilitate proof-reading, leave ample space, at least two centimetres of empty space surrounding the text on the page and the text double-spaced. Decide which English language you should use and adhere to it. American-English is a separate language, not a dialect, mixing languages is therefore rude to both nationalities. Many pitfalls are described in the highly recommended (and very funny) The Economists Style Guide, which is available on the www. The Fundamental rule of good writing: Revise, revise and revise. You have to convince potential readers quickly, therefore convey your message e¢ ciently! Most readers will scan the paper –not read it, you must therefore help readers minimise time spent on your paper. This is done by, catching the reader’ eye with an interesting title and clear structure. s 4. STRUCTURE The structure of the paper should at least contain: Title, Abstract, Introduction, Conclusions, Acknowledgements and References.
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4.1.
Title
Paper titles should attract attention: Pollution Havens and Foreign Direct Investment - Dirty Secret or Popular Myth?, What determines why and how much people tip in restaurants?, Is Hungary ready for in‡ ation targeting? Do public investments crowd out private investments? Fresh evidence from Fiji. Nord Pool: A Power Market without Market Power. 4.2. Abstract
The Abstract should attract potential readers. It should not be longer than half a page and max. 100 words and should contain: Background, Purpose, Model-approach, Results and Conclusions. About one sentence on each point approximately …ve sentences. An example: In recent years several models have been proposed to estimate time-varying technical e¢ ciency. These models di¤er to a great extent in speci…cation and estimation. This paper undertakes a comparison between di¤erent speci…cations proposed in earlier research. The models are used to estimate the technical e¢ ciency of 15 Colombian cement plants observed during 1968-1988. The e¢ ciency scores and the time path of e¢ ciency are found to vary substantially across models. JEL Classi…cation: C23, C52, D24, L61 Keywords: productive e¢ ciency, stochastic frontiers, time-varying e¢ ciency, panel data, cement industry 4.3. Clear structure
For an applied paper: Introduction; Previous research (short if not in introduction); Methodology; Theoretical model; Calibration (Econometric speci…cations, Stochastic assumptions, Estimation procedures); Data with Summary statistics; Empirical results (Statistical …t, Speci…cation tests, Robustness-sensitivity); Conclusions; References. 4.4. Body of the paper
Keep it down to a few sections. Try to get it short and keep the structure clear and wellbalanced. Typical problems: paper too long: max 30 pages double-spaced, excluding Tables and Figures; the string of paragraphs do not give a clear structure; too many Tables and / or Figures; policy conclusions (if any) are missing. 4.5. How to write Introduction and Conclusion
The Introduction is the most important part of the paper as well as the most demanding part of the paper. It should clearly state: what the problem is, why it is important, what has been
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done so far, what is your value added is (a better estimation, method, data set, model. . . ), what your …ndings are, what the structure of the paper is. Major points: place your work in the context of the existing literature, describe your main …ndings. Do not start with a three-page survey of the …eld – your reader will want to know your contribution sooner than that. Give priority to the development of ideas – not who did what, albeit, that must also be included. Your contribution in relation to this should be unambiguous. Be fair and refer to relevant background papers, especially surveys. Only relevant references –no name dropping. Use plain language and general concepts –no technical details. It must contain: the purpose (objective) of this paper is. . . . . . , the contribution of this paper is. . . My (our) major contribution is. . . ., the content of the paper (the paper is organised as follows.). Important to check how your paragraphs …t together –the sequence of paragraphs is very important in the introduction –try to get a convergence to the main point: your own objective. An example: The speci…cation and estimation of productive e¢ ciency has evolved rapidly during the last decades, and there are a large number of di¤erent approaches, deterministic, stochastic, parametric and non-parametric, applied in empirical research. While most studies are based on cross-section data, there is an emerging set of empirical applications based on balanced or unbalanced panel data. Because such data will provide a much more detailed evaluation of the relative performance of micro units, linking e¢ ciency to productivity and technical change, are of great value. A crucial issue in panel data modelling is the speci…cation of e¢ ciency and technical change. Such a speci…cation reveals the time path of e¢ ciency for the micro units answering questions about the degree of stability in e¢ ciency scores and whether ine¢ ciency is a transitory or permanent state. Especially in the stochastic frontier literature, which is of concern here, several approaches are suggested. Panel-data models in the stochastic frontier literature can be divided into two main groups. The …rst group assumes technical e¢ ciency to be time-invariant; see Pitt and Lee (1981), Schmidt and Sickles (1984), and Battese and Coelli (1988), among others. The second group allows technical e¢ ciency to be time-varying; see Cornwell, Schmidt and Sickles (1990), Kumbhakar (1990), Battese and Coelli (1992), Lee and Schmidt (1993). Each of these two groups can be further subclassi…ed depending on whether or not any distributional assumptions or functional forms are imposed on the error components In the literature on stochastic frontier functions, several models are proposed to allow technical e¢ ciency to be time-varying. However, in the empirical literature on the estimation of production frontiers using panel data, the issues of model speci…cation and selection of various speci…cation forms are rarely emphasized.
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In this paper we consider the issues related to the speci…cation and estimation of various models incorporating time-varying technical e¢ ciency. First, we present and estimate three di¤erent model speci…cations. Second, we analyse the bene…ts and limitations of the di¤erent speci…cations and quantify the impact of these on the results obtained. Third, in the empirical part, we use unbalanced panel data from the Colombian cement industry, observed over the period 1968-1988, to compare the productive performance of the plants in terms of input elasticities, returns to scale, technical progress and technical e¢ ciency measures. A priori, the choice between time-invariant and time-varying technical e¢ ciency is dependent upon technological and the recent surveys of the frontier literature are found in Lovell (1993), Greene (1993), and Heshmati (1994). Because of the lack of a well-established theory that generates a certain structure of …rm ine¢ ciency, the speci…cation of ine¢ ciency in frontier modelling is usually ad hoc and based on tractability rather than on a theoretically derived ine¢ ciency generating mechanism. In the literature, however, there are a few old stylized models which generate a certain time path for the development of technical e¢ ciency of a productive unit; see Hjalmarsson (1973) and (1974), and Forsund and Hjalmarsson (1974) and (1987). First, in a Manne-type capacity-expansion model of the putty-clay type, with economies of scale ex ante and a growing demand for output, but no technical progress, a certain productive unit becomes gradually less e¢ cient as economies of scale are gradually more exploited in new capacity; see Hjalmarsson (1974). At the same time the e¢ ciency structure may be fairly constant. Second, the same holds in a putty-clay model with embodied – but no disembodied – technical progress as new technology is picked from the ex ante production function. Third, a putty-clay model without technical progress or scale economies in the ex ante production function generates a gradual compression of the e¢ ciency structure, since when all units are renewed they will pick technology from the same constant ex ante production function. In this case, the e¢ ciency of a certain unit will remain constant until there is a jump in the e¢ ciency score from worst practice to best-practice when an old unit is replaced by a new one. Fourth, a "su¢ cient" condition to keep e¢ ciency time-invariant in a putty-clay model is the presence of disembodied technical progress at a rate that compensates for embodied technical progress and scale economies in the ex ante function. Outside the stylized models, the presence of disembodied technical progress may give fewer ine¢ cient units a chance to catch up with the frontier units as these are gradually improving. Elimination of organisational slack may compress the e¢ ciency distribution, while generation of slack works the opposite way. Thus a priori, only under
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strong assumptions could we expect e¢ ciency to be time-invariant. The main reason for our choice of the cement industry is that it approximates a putty-clay industry quite well. The basic technology is embodied in the cement kiln, the design of which is decided at the investment date. Technical progress is characterised by capitalembodied energy-saving progress, while labour-saving progress seems to be of a more disembodied or gradual nature; see Forsund and Hjalmarsson (1983). The paper is organised as follows: In the next section the stochastic frontier production function models with time-varying technical e¢ ciency are presented. Section 3 contains the speci…cation tests and the empirical results, along with a comparison of the performance of the di¤erent model speci…cations, while Section 4 summarises and draws conclusions. The Colombian cement data is described in Appendix. 4.6. Conclusion
Repeat what the problem was and give compact summary of your results. Indicate clearly what your contribution is and a statement of the main lesson to be drawn from your analysis. Address open points and promising directions for future work. An example: In this paper we have focused on labour productivity and the relative performance of public and private utilities in Swedish electricity retail distribution during 19701990. Because in electricity distribution the choice of output measure is a controversial issue, we consider a hedonic measure of output which is constructed from outputs, their qualities/attributes, and network variables. The estimation is based on a large sample of panel data on privately owned …rms, municipal utilities, municipal companies and companies with mixed ownership during this time and we examine economies of scale, technical change, and relative e¢ ciency in labour use across ownership categories. Empirical results show that: Privately owned …rms are relatively more e¢ cient and the relative e¢ ciency of municipal companies has deteriorated rather much over time according to the average production function but improved slightly at the frontier. The results are much the same for municipal companies at the average function, while the time development at the frontier is rather uneven. Mixed ownership …rms improve relative e¢ ciency at the average function but show an uneven development at the frontier. In the stochastic frontier models municipal utilities are more e¢ cient than mixed ownership …rms most years while the opposite holds in the deterministic DEA models. In general, for the mean of all the …rms as well as for each ownership category, increasing returns to scale are observed most years. An exception is the mixed ownership category which shows decreasing returns to scale all years in Model 1 and this 6
is also the case in Model 3 after 1979. In all models, scale economies are found to be highest for the …rms under municipal utilities, except for some years with very high mixed ownership values. In contrast to the substantial variation in returns to scale across models, there is very little variation in the rate of technical change between di¤erent models. There is a slowly declining trend in technical progress from the range 2-3% per year down to the range of 1-2% per year. The di¤erences in technical progress between di¤erent ownership categories are small. The persistent e¢ ciency di¤erences between private and publicly owned …rms, we interpret as a strong indication of the impact of yardstick competition. However, this yardstick type of regulation seems to o¤er weak incentives for cost minimisation in the municipal …rms located in densely populated regions. 4.7. Be generous! An example: The paper is written as part of the Norwegian Research Council program E¢ ciency in the Public Sector at the Frisch Centre, University of Oslo. It was …nished while the …rst author was a visiting fellow at ICER, Turin. Additional support from the following sources is gratefully acknowledged: The Bank of Sweden Tercentenary Foundation, HSFR, Jan Wallander’ Research Foundation and Gothenburg School of Economics s Foundation. We are indebted to Anders Hjalmarsson for carrying out all programming and calculations. The paper has been greatly improved due to comments from referees and special issue editor. 4.8. References Acknowledgements
Be fair and refer to relevant background papers, especially surveys. Only relevant references – no name dropping or “opportunistic” references. Check you statements carefully – who wrote what. Refer to good recent surveys, check year, pages, spelling, etc. carefully. Make sure that there is a one-to-one mapping between your citations and references. 5. ONCE THE DRAFT IS FINISHED Do NOT submit it to your supervisor: Read and revise a few times then put it aside for a week. Read and revise again, then submit it. Your supervisor has probably read thousands of articles, if he / she does not immediately understands what you want to achieve, no one else will. Good luck.
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