How to write

Ståle Navrud

Department of Economics and Resource Management Norwegian University of Life Sciences E-mail: [email protected]

Microdis Annual Meeting Feb. 25-27 2009

Outline

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Before we start writing Two Fatal misunderstandings Writing = research General rules The outline of a paper

– the

macro

level

Before we start writing

1.

Codebook

for Microdis Core and Extended Questionnaire for health, social and economic themes to ensure

comparability

- across sites within a country - across countries for

each

thematic area - Same question coded the same, even if numbered differently in different sites and countries - If reply options added and/or changed in some countries; code the reply option which are similar in the same way groups of options – and if different options; try to classify reply option into common - Countries that have already coded their surveys could act as the model for how to do it (but could develop a new protocol as it is easy to re-code according to a new protocol) - Put detailed data into the database, and later merge data in standardized variables (the other way around is not possible!)

Before we start writing (cont.)

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Central Database - all teams deposit their dataset (coded according to the same codebook ) - central database accessible only to the MIcrodis teams - should also contain the codebook(s) themselves and the questionnaires from all countries (original version in Englisgh, translated / adapted versions in all languages and the ”translated-back-to English” versions)

Before we start to write (cont.)

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Rules for Authorship and Publications - national teams can publish based on data from their site with PI as lead author and all involved as co-authors - list of possible publications; each with a LEAD author responsible for progress and final paper; co contributions (i.e. write/comment on content).

authors can ”sign on” for contributing to the paper , but must be actual - thematic papers across comparable sites (same type of diaster, same recall period etc.); both within a country and multi-country comparisons - one overall multi-country paper with co-ordinator Debby as lead authors and all PIs as co-authors about the lessons learned from developing the Microdis tool - an integrated, inter-disciplinary tool # 1, 2 AND 3 NEED TO BE DONE QUICKLY , AND BY APPOINTED RESPONSIBLE INSTITUTIONS/PERSONS  To be put in the DoW

Two fatal misunderstandings

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“Write up research” • Writing is research!

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”That’s just a matter of style, after all it’s content that matters” • Good content and poor style do not sell • Style and content cannot be separated

Why is “writing = research”?

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• • • • Structure the problem • The paper outline is a research plan ‘The devil is in the details’. Writing reveals : That you did not understand the problem That your research was incomplete Forces you to think logically through problems New ideas

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Why write?

Writing = research • • • • The article is the principal means of scientific communication You should talk with your colleagues! Work is useless unless known to others Stimulate debate and further work Benefit poor people (Improve Disaster management ) EU projects are evaluated based on deliverables

and publications

• • • Personal carrier Build a reputation Get a good job Be invited to workshops

How to start?

• • • Publish when you have something to say Write early rather than late •

But

don’t fall in love with your first draft – some should be thrown into the dustbin • Cut! For example: long literature reviews Target a paper for a conference • Tie yourself to the mast

How to start?

• • • Start with one paper, not the full theses You can do it!

• By definition, a PhD thesis paper is worthy of publication • A lots of poor articles published - you can do better Writing is an art that can be learned • Listen & read – be an active learner

• •

Rule 1: Be Clear

“The one genuine rule, a golden one, is

Be Clear

” (McCloskey) Clarity: • Focus on the key point (argument) • Test question: does this paragraph contribute to my main point? If no: Delete!

• What’s the point?

• Test question: What is my main arguement? Write it down in simple language!

• Be concrete & specific • Definite & unambiguous

Simplicity

• Science

vs.

journalism • •

Journalism

= Simple without understanding

Science

= Simple with understanding Do things as simple as possible, but not simpler (Einstein) Simplicity is the ultimate sophistication (Leonardo da Vinci)

• •

What is ’unclear’?

“The completeness disease” • Side tracks & distractions • Data dumping & name dropping The risk averse approach (safeguarding) ”Poverty and environment interact in a complex way where the outcomes are highly context specific.” • Ambiguous sentences, vague statements, e.g.: maybe, etc., Too vague to be right or wrong (economic proverb)

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Rule 2: Originality

Journals publish significant, original research

What makes the paper original = new?

• New topic?

• New theory?

• New methods?

• New data?

Typical: Old - but small twists on - topic, theory and/or methodology, but with new data •

The scientific method is to test respected theories against new data

Test question: What do I add to the literature? It’s a lot of new and good things in this paper. Unfortunately, what is good is not new, and what is new is not good (anonymous referee comment)

Rule 3: Significant

• • • Significant = Important to • life of people • policy makers • researchers Put the paper in context; draw the link to broader issues • Why is disaster assessment in India important to the world?

Test question: What should the policy makers, researchers or other audiences do differently?

Significance is determined by how it changes the thinking of the research community (Garcia and Nelson, 2003)

Rule 4: Less is more!

• Keep it short & simple

The paragraph

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Use paragraphs as the unit of composition

Each paragraph should have (only) one point • Hint: Number the paragraphs in you first drafts The classical paragraph: • Declaration • Elaboration • Conclusion

Three types of papers

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The theoretical/analytical paper The essay 3.

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The classical science paper

Analyzing and testing theories on new data

The outline of a paper – the macro level

• • • • • • • Title Abstract Introduction Theory and Methods Results Discussion Conclusions (and Policy Recommendations)

Title

• • • The first trigger The first – and often the last – a reader will see of your paper Informative • Get the keyword in the title • A key result: •

Not:

The effects of reduced impact logging on water quality, quality

but

• Reduced impact logging maintains high water

Examples Forest Management

• • • • • • • • • • From Mao to markets in China's forests Globalizing local communities The conservation of donors Disturb forests for their own good Certifying the little guys Tacos, tequila and community forests Chainsaws in the drugstore Will the eucalyptus eat your children?

Filipinos 'think locally, act locally’ Poverty and the wild beasts

Abstract

• • Most people only read the title and abstract: What do you want to tell them?

• What was studied, the main finding, and conclusion (policy implications?) • The key argument • Limit description of methods It’s the second trigger

Example

Researchers have long argued that improved livestock technologies and intensification will reduce the pressure on Latin American forests. This article combines economic theory with insights from seven case studies to examine under what conditions technological change will reduce (increase) the pressure on forests. In many contexts improved technologies, by making cattle production more profitable, will result in

more

forest being converted to pasture. Silvopastoral systems and other labor-intensive practices can restrain pasture expansion, at least in the short-run. Unfortunately, in most cases ranchers will only be willing to adopt such practices when land has become scarce and most forest is gone.

1. Introduction

• • A good introduction: • What is

new?

• Why is the topic

important?

• Focus on the main argument • Short (skip the outline paragraph?) A bad introduction • Too long • Either

too

specialized or

too

general • Long descriptions (backgrounds)

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Examples

“No” starters: • “This paper discusses ….

• “Poverty is widespread in Ethiopia …. + long background of well known facts ….

Better ones are: • “Does market integration destroy community management of forests? XX has argued … In this paper I demonstrate, quite the contrary, that ….

• “Poverty is commonly believed to be a major cause of tropical deforestation. This paper gives evidence from Sumatra that questions this view…

Example (Arrow and Lind, AER 1970)

”The implications of uncertainty for public investment decisions remain controversial. The essense of this controversial is as follows: …. The issue is whether it is appropriate to discount public investments in the same way as private investments.”

(2. Background: study area, literature, current debate,...)

• • • • Many readers skip it. They’re interested in the new stuff Can be part of introduction Often too much irrelevant Can be useful to write it down, but delete from the final draft

3. Theory

• A literature review or a proper formal model • worst case: trivial, standard model • One possibility: a simple optimization model adapted to the problem • Derive testable hypotheses

4. Data and methodology

• • • • Describe data, data collection methods, sample, etc. Justify method Only descriptions Typical mistakes: • Too much on basic methodologies • Too little on data (collection)

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5. Results (and discussion)

The actual findings Focus on findings relevant to the topic & hypotheses Tables are often overloaded Use appendices Figures are generally better than tables

Results (cont.)

• • Avoid ”verbal math” • Don’t write what’s already in the tables ”The variable CREDIT has value of 6.0567 and a t-statistic of 2.2876, and is therefore significant at the 5 % level. The analysis shows that an increase in the CREDIT variable increases maize production by more than 6 units.” Economic significance ”The findings suggest that providing credit to farmers increase production by 24 %, and overall income by 17 %. … Providing credit to all farmers will make the share of population below the poverty line to drop from 56 % to 42 %.”

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6. Discussion (can be included in results)

• • The broader interpretations. What explains the findings?

Relate to hypotheses & theory!

Relate to the literature: what are the new things suggested?

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7. Conclusion

Main conclusions brought together • • Implications & recommendations Research (but don’t beg for more research) Policy • • Typical mistakes: Repeat introduction & abstract Unfounded conclusion

What’s the important parts?

• • How people read a paper: • Title • Abstract & keywords • Figures and Tables • Conclusion • Results • Discussion • Rest of paper Write the introduction and conclusion at the end, and spend lots of time on that!

Important parts

COMMON PERCEPTION OF THE IMPORTANCE OF DIFFERENT COMPONENTS OF A PAPER ACTUAL IMPORTANCE OF DIFFERENT COMPONENTS OF A PAPER

TITLE ABSTRACT FIGURES TABLES RESULTS THE REST

Take home messages

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Clear (= focus) New (= original) Important (= significant) KISS (= Short and Simple)