Frequently asked questions

IZA World of Labor contributions are framed as policy papers, hence we have limited the number of in-text citations while keeping a more comprehensive list of scientific papers that are also relevant for academic readers. There are three types of references: “further reading,” “key references,” and “additional references.”

Further reading contains literature that is relevant for the interested, non-academic reader. It can include journal articles, reviews and more general books and articles. This reading is usually not cited in the text.

Key references are the most important academic papers a (non-specialist) reader should know about. They are cited in the text and numbered [1], [2], [3]..., etc. in the order that the paper first appears in the text.

Additional references contain a list of all scientific papers that would be cited in a purely academic article, in addition to the key references. This list includes scientific papers that are relevant to academic and specialist readers and provides the basis for the content of the evidence map. These papers are not cited in the text but will be listed online in the right-hand column of the paper following the key references.

The full list of references, comprising further reading, key and additional references, can be viewed and printed separately. 

Each IZA World of Labor article has a map that indicates for which countries empirical evidence on this specific topic exists. The list of key and additional references provided in the article provides the basis for this map.

If empirical evidence exists for one particular country, that country will be shown in a different color, varying from yellow to different shades of green. The color used indicates the country’s development status based on the country classification (see the FAQ "What do the different colors for each country mean on the evidence map?", for an explanation of these classifications).

The number shown inside the pin indicates how many relevant academic studies address this policy question. If you click on the pin, an overlay pops up that shows the key and additional references for an article.

The Institute for Labor Economics (IZA) recognizes the importance of proper citation of data for the following reasons:

• acknowledges the author's sources;
• makes identifying data easier;
• promotes the reproduction of research results;
• allows the impact of data to be tracked.

It therefore developed a data citation convention, which takes into account prior work done by respectable institutions.

If original data are used in an IZA World of Labor article, e.g. in the graphical abstract or in figures and tables in the main text, authors are asked to follow the citation rules defined in the IZA World of Labor data citation convention.

In addtion, IZA's Research Data Center (IDSC) offers the IDSC Dataverse, a data, metadata and code repository for labor and behavior economics. IZA affiliated entities such as projects, institutions or journals as well as individual authors may request their own sub-dataverse within the repository as well as deposit their data to satisfy funding or journal requirements adhering to the Open Science principles. On the other side data is then made available for academic purposes such as teaching, secondary research and replication. Each data set deposited will be issued with a DOI to make it uniquely identifiable and citable. For support please contact idsc@iza.org.

For each IZA World of Labor article we list data and method information for each of the key references. The data information includes the institution and DOI or URL of the data source (where available), the type of data collection and the data dimension (breadth and depth).

The type of data collection distinguishes:

1. Administrative data (micro data)
2. Census and microcensus data (micro data)
3. Survey data (micro data)
   3.1 Household data
   3.2 Firm data
   3.3 Other (including matched employer-employee data)
4. Experimental data (micro data)
   4.1 Laboratory experiments
   4.2 Field experiments
   4.3 Quasi-natural experiments
   4.4 Natural experiments
5. Other (including e.g. aggregate data, transaction and textual data, and data collected from the web)

Individual data are micro data and are classified in the context of data collection. Other data are all other types of data, including aggregate data, transaction data, and textual data.

The data dimension distinguishes:

1. Cross-sectional data
2. Time series data
3. Longitudinal or panel data

On the Data sources page you will find a list of data sources that are used in the underlying scientific papers that support our IZA World of Labor articles. 

When there is empirical evidence for one particular country, that country is colored to indicate how it is classified according to the classifications used in The Global Competitiveness Report (GCR) 2014–2015 (p. 11) by the World Economic Forum’s (WEF) Center for Global Competitiveness and Performance. A country that is not categorized in the GCR will be colored gray.

The GCR is the flagship publication of the WEF and it gives a detailed assessment of the “productive potential [/competitiveness] of nations worldwide,” in particular of 144 economies in its 2014/2015 volume. The authors of the study define competitiveness as “the set of institutions, policies, and factors that determine the level of productivity of a country” (p. 4). Their productivity measure thus goes beyond the differentiation between “more,” “less,” or “least developed regions” such as given by the United Nations , for instance, or “lower,” “lower-middle,” “upper-middle,” and “higher-income economies” such as in the World Bank Income Groups.

There are three different classification of countries: those with factor-driven economies, those with efficiency-driven economies, and those which are innovation-driven.

Factor-driven economies are those where developing basic requirements are still key for development and success e.g. institutions, infrastructure, macroeconomic environment, and health and primary education.

Efficiency-driven economies are those where developing efficiency enhancers, such as higher education and training, efficiencies in goods and labor markets, developing a financial market, improving technical readiness, and increasing market size, is key.

Finally, innovation-driven economies are those where the focus is on developing business sophistication and innovation.

For information on the color coding for countries, see FAQ "What do the different colors for each country mean on the evidence map?" 

The search works by looking through all the information on the site (including articles, videos, and author biographies), finding every instance of the word that is being searched for. A search can also return results that include IZA Discussion Papers (IZA DP) and IZA Policy Papers (IZA PP).

Please note that the search cannot look for hyphenated words.

The search returns responses according to the level of relevance, according to the following weighting: articles (five times more important than any other content) then keywords (three times more important than any other content).

The advanced search allows you to sort results more specifically:

• by content type so you can look in one particular area, e.g. just in articles, just in videos, or just in authors.
• by keyword.

The left-hand column categorizes all the results found according to author, and subject area. The numbers in brackets indicate the number of articles found for each category for the current search enquiry.

Conflicts of interest exist if authors have financial, personal, professional, political, institutional, religious, or other relationships – such as employment, consultancies, and stock ownership, honoraria, paid expert testimony, and travel grants – with other people or institutions that a reasonable reader would like to know about in relation to the contribution.

It is not our aim to discourage research interaction with practitioners and policymakers – quite the opposite. However, those interactions, if not appropriately disclosed, can raise questions about whether they have influenced the conduct of research and biased the interpretation of results.

It is hence important to fully disclose all actual and potential conflicts of interest. Authors are therefore asked to disclose any relevant (in relation to the contribution) and material (if its value exceeds US$5,000 per year) financial relationships within the last three years.

Before declaring there are no competing interests, please consider the following cases:

• Have you received any money, directly or indirectly (fees, salaries, funding) from an organization which could financially gain, or lose, from the publication of this contribution, now or in the future? 
• Do you hold stocks, shares or options with a company which could gain, or lose, financially from this publication, now or in the future? 
• Are there any non-financial conflicts of interest, such as personal, political, religious, ideological, intellectual or commercial interests? 

For further information, please also see the IZA's Guiding Principles of Research Integrity.

IZA World of Labor articles can be cited in the following way:

Smith, N. Gender quotas on boards of directors. IZA World of Labor 2014: 7 [doi:10.15185/izawol.7]

Later versions of the same article can be cited as follows, for example:

Smith, N. Gender quotas on boards of directors. IZA World of Labor 2016: 7.v2 [doi:10.15185/izawol.7.v2]