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LIS: Cross-National Data Center in Luxembourg www.lisdatacenter.orgwww.lisdatacenter.org (new URL!) Janet Gornick, LIS Director Gender Statistics and Tools.

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Presentation on theme: "LIS: Cross-National Data Center in Luxembourg www.lisdatacenter.orgwww.lisdatacenter.org (new URL!) Janet Gornick, LIS Director Gender Statistics and Tools."— Presentation transcript:

1 LIS: Cross-National Data Center in Luxembourg www.lisdatacenter.orgwww.lisdatacenter.org (new URL!) Janet Gornick, LIS Director Gender Statistics and Tools for Gender Analysis The World Bank / April 20, 2011 9:00-1:00PM MC-C2 125

2 Today’s program Part I. Overview of LIS: Data and Access Part II. Introduction to a Set of National Indicators Designed for Gender Analysis World Bank: “Key Gender Employment Indicators” (KGEI) LIS: “Employment Key Figures by Gender” Part III. KGEI: Some Illustrative Results

3 Part I Overview of LIS: Data and Access

4 What is LIS? LIS is a cross-national data center, located in Luxembourg. LIS is a physical venue with secure servers in Luxembourg as well as a virtual venue for conducting research. LIS is home to the Luxembourg Income Study Database and the Luxembourg Wealth Study Database. These databases contain harmonised microdata from high- and middle- income countries around the world. Our mission is to enable, facilitate, promote, and conduct cross-national comparative research on socio-economic outcomes and on the institutional factors that shape those outcomes. LIS also has a satellite office at The City University of New York (CUNY).

5 ’ LIS’ goals ● to harmonize (“lissify”) cross-national microdatasets that have been collected from participating countries on income/wealth, and their components, along with demographic and labor market data; ● to provide a secure method that allows researchers to access data that would otherwise be unavailable due to country- specific privacy restrictions; ● to create and maintain a remote-execution system that receives research requests (program code) and returns results to users at off-site locations ● to make national indicators available via online table-making options  today’s focus ● to promote cross-national research on the economic and social wellbeing of persons and households.

6 The Luxembourg Income Study (LIS) Database since 1983 The LIS Database now includes microdata from 40 countries, mostly in Europe and North America, but also including Australia, Israel, Korea and Taiwan – and, as of 2009, six Latin American countries. The LIS Database includes (mainly) income, employment, and demographic data – available at the person and household levels. The LIS Database contains over 200 datasets, organized into six time periods, known as waves, spanning the years 1968 to 2006. The next major addition will be a group of middle-income countries. (I will come back to this).

7 The Luxembourg Wealth Study (LWS) Database since 2007 We established a network of producers of microdata on household wealth and, modeled on the LIS Database, we harmonized country- specific microdata into a common template, including measures of net worth and its components. The LWS Database includes (mainly) wealth, debt, income, employment, and demographic data, at the household level. The LWS Database now contains microdata from 12 countries (Austria, Canada, Cyprus, Finland, Germany, Italy, Japan, Luxembourg, Norway, Sweden, UK, US). Over the next 2-3 years, we will work with several international organizations to set guidelines for wealth data collection and measurement, as LIS has done with income data.

8 Access to the data – three pathways First: Remote-execution system (“LISSY”) This is the primary means of access; it uses a software system that was designed specifically for LIS. Researchers write programs (in SPSS, SAS, or Stata) and send them via email directly to the LIS server; results are returned to the researcher, with an average processing time of under two minutes. This is LIS’ “claim to fame.” Access is granted to non-commercial researchers in financially-contributing countries/institutions. ►All WB staff have unlimited free access until 31 December 2011. Stay tuned for an update.

9 Second:Web Tabulator The LIS Web Tabulator allows registered users to make tables on-line, using keywords. Users can generate research-specific cross-national comparisons without the need for programming. Currently, the included data are all at the household-level for now, and are thus of limited use for gender analysis.

10 Third:Key Figures - two sets of standardized national indicators Inequality and Poverty Key Figures The Inequality and Poverty Key Figures include multiple inequality measures (e.g., Gini and Atkinson coefficients, percentile ratios), relative poverty rates for various demographic groups, and median and mean disposable household income. These Key Figures are constructed for all LIS datasets, in all waves. Employment Key Figures by Gender  today’s focus The Employment Key Figures by Gender are a set of national-level indicators presented in ten tables. These figures highlight women’s economic outcomes and gender inequality in poverty and employment. These Key Figures are now available for all datasets in LIS’ Wave V (2000) and VI (2004).

11 Research based on the LIS/LWS Datasets LIS/LWS data users come from diverse disciplines, including economics, sociology, political science and the policy sciences. Since the founding of LIS, our microdata have been used by nearly 2500 researchers. Many researchers use the data to analyze variation in socio- economic outcomes within and across countries. The data are often used to study the effects of economic and social policies on outcomes – including income poverty, income inequality, employment status, wage patterns, wealth levels/portfolios, and family formation. About one-third of the LIS/LWS research in the last ten years has been focused on questions about the economic status of women and their families; a core focus is gender inequality in employment.

12 Distribution of LIS/LWS research Research based on the LIS/LWS data: ● is catalogued in the LIS Working Paper* series, which currently includes nearly 600 papers (papers are searchable by author, year, country [data], and/or keyword, and downloadable); ● has appeared in many policy reports, graduate dissertations, journal articles, and books; ● is often featured in the popular media.

13 What’s next? ● Inauguration of new LIS website; to be launched in 2 weeks www.lisdatacenter.org ● Completion of LIS Database Wave VI (centered on 2004). Thirty datasets are now up. ● Acquisition and harmonization of LIS Database Wave VII (centered on 2007). Introduction of revised template. ● Continued expansion of LWS Database. Soon we will add Spain.

14 Priority: adding more middle-income countries ● The great majority of countries now included in the LIS and LWS Databases are high-income countries. ● The current LIS Database currently includes eight middle-income countries: Brazil, Colombia, Guatemala, Mexico, Peru, Romania, Russia, and Uruguay. ● Over the next 3-5 years, we will add several more middle-income countries. We now have datasets in-house from India, South Africa, and Chile; we have secured agreements with China, Egypt, and the Palestinian Authority; we are negotiating with Serbia, Croatia, and Viet Nam; this spring, we will approach Bolivia, Costa Rica, Dominican Republic, Ecuador, Panama, and Paraguay. Stay tuned!

15 Part II Introduction to A Set of National Indicators Designed for Gender Analysis World Bank: “Key Gender Employment Indicators” (KGEI) LIS: “Employment Key Figures by Gender”

16 An online demonstration http://www.lisdatacenter.org/data-access/key- figures/employment-by-gender/ Data / access: A. Search online B. Download Excel files Documentation: Detailed documentation files are online. See links to “table notes” and “column notes”. World Bank website: http://go.worldbank.org/A2LTZUHGL0

17 Part III KGEI: Some Illustrative Results

18 Figure 1 Employment rates of men and women in a partnership (%). The effect of having children.

19 Figure 2 The gender earnings ratio (female earnings/male earnings)

20 Figure 3 The gender earnings ratio, by parenting status

21 Figure 4 Youth employment

22 Figure 5 Employment rates of men and women (%) and the gender earnings gap

23 Figure 6 Female/male employment ratio by number of children


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