Research Data Center of IZA (IDSC)
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Replication Data for: 'Sexual Harassment and Gender Inequality in the Labor Market'
No full textThe data and programs replicate tables and figures from "Sexual Harassment and Gender Inequality in the Labor Market", by Folke and Rickne. Please see the README file for additional details
Replication data for " Schools under mandatory testing can mitigate the spread of SARS-CoV-2"
No full textThis dataset contains replication data and code for " Schools under mandatory testing can mitigate the spread of SARS-CoV-2", based on publicly available case and death counts of SARS-CoV2 in Germany
Replication Data for: Nostalgia in European Party Politics: A Text-Based Measurement Approach
No full textReplication data and scripts to reproduce all plots, tables, and analyses reported in the paper and Online Supporting Information. The file 00000_README.pdf contains detailed information on each script and explains how to run the files.
The PolNos datasets are available at: Müller, S. and S.-O. Proksch (2023). PolNos: Political Nostalgia in Party Manifestos. Harvard Dataverse, V1. URL: https://doi.org/10.7910/DVN/L198GI
The Internal Economics of the Firm: Evidence From Personnel Data
No full textThe dataset contains confidential computerized personnel records for all management employees of a medium-sized U. S. firm in a service industry over the years 1969-1988. The principal investigators use these data to peer inside the "black box" of the firm to explore the existence and nature of the internal labor market and the wage policy of the firm.
The researchers obtained the firm's yearend backup personnel tapes, which included current information on every managerial employee in the firm as of December 31 of each year. Each observation contains an employee 1D number, age, sex, race, education, job title, cost center description, cost center code, salary, bonus, salary grade, and performance rating. Eight job levels from entry management (level 1) to Chairman-CEO (level 8) were clearly identified from analysis of the job titles. Seventeen titles out of over three hundred constitute a large share of employment. Levels 1-4 contain the bulk of managers, as the hierarchy narrows considerably from levels 4 to 5. All salary data are in local currencies. Not all variables are available for all years or records, although on the whole the dataset is complete. There are two major exceptions:
Bonusdata cover 1981-1988. Also, titles were not coded for some new hires in the last years, though other variables were. Thus, assignment of these employees to levels was impossible in those years. This is an insignificant problem except in 1987-1988, in which roughly 10 percent of employees and half of new hires did not have title data. These missing data mean that researchers must handle inferences from title and level data in the last few years with some care. Where the data report pooled results, the project have always calculated the statistics over 1969-1985 to test for robustness of inferences.
The timing of the variables is worth noting. Salary, title, performance rating, and other variables are year-end values. The project does not know when during the year pay or title changes occurred or ratings were given, so these variables may not be exactly concurrent. In the statistical work the researchers assume that title changes, pay changes, and ratings occur simultaneously.
Finally, for entry or entrants into the dataset it is unclear in what year those in the dataset in 1969 actually entered the firm. In addition, it is not possible to tell whether new entrants in any year are new hires at the firm; they could have been promoted from clerical to management positions.</p
Replication data for: "Born to Lead? The Effect of Birth Order on Noncognitive Abilities"
No full textReplication data for: "Born to Lead? The Effect of Birth Order on Non-Cognitive Abilities
Replication Data for: "Canary in a Coal Mine: Infant Mortality and Tradeoffs Associated with Mid-20th Century Air Pollution"
No full textReview of Economics and Statistics: Forthcoming
Replication data for: [Public Health Policy At Scale: Impact of a Government-sponsored Information Campaign on Infant Mortality in Denmark]
No full textDocumentation file for do-files and datasets corresponding to paper titled:
“Public Health Policy at Scale: Impact of a Government-sponsored Information Campaign on Infant Mortality in Denmark”
Onur Altindag, Jane Greve, and Erdal Tekin
This document describes the datasets, STATA and R programs that replicate the results for the paper “Public Health Policy at Scale: Impact of Government-sponsored Information Campaign on Infant Mortality in Denmark” by Onur Altindag, Jane Greve, and Erdal Tekin, Review of Economics and Statistics, the version that is accepted on February 2021
Longitudinal Survey on Rural Urban Migration in China
No full textThe Longitudinal Survey on Rural Urban Migration in China (RUMiC) consists of three parts: the Urban Household Survey, the Rural Household Survey and the Migrant Household Survey. It was initiated by a group of researchers at the Australian National University, the University of Queensland and the Beijing Normal University and was supported by the Institute for the Study of Labor (IZA), which provides the Scientific Use Files.
RUMiC was established to study the patterns and effects of migration in China and was designed to provide a longitudinal dataset covering a five-year time span.
It collects data on three populations:
- Rural households both with and without migrants (through the Rural Household Survey)
- Urban resident households (through the Urban Household Survey)
- Rural-to-urban migrants (through the Urban Migrant Survey)
The research topics of the RUMiC comprise the welfare status of migrants: their jobs, incomes, physical and mental health, their children's education and health, and the extent to which they assimilate into their city communities. The questionnaires obtained individual- and household-level information.
The individual-level component covers four areas:
1) Household composition
2) Adult education
3) Adult employment
4) Children
The household head answered questions covering:
1) Social networks
2) Lifecycle events
3) Household income
4) Household assets
5) Housing conditions
6) Information on the rural home village
The employment section focuses on the labor market performance of adults. Different questions were asked to salaried workers, the self-employed and unemployed. For the Migrant Survey, selected questions were also asked regarding migrants' first job in the city.
Children's module surveys children aged 0-15 or over 15 but still at school. The Migrant Survey covers both children who live in the city with their parents and those left behind in the countryside. The Rural Survey only covers children whose parents did not migrate. The same questions are used in both surveys.
The social network section contained several sub-sections covering also the network of spouses not present in the household, of children aged over 15, of the parents of both the household head and the spouse. Questions also cover the employment and education status of up to five closest contacts.
The survey locations are primarily based on whether a province is one of the major sending or receiving regions. The Rural Household Survey was conducted in 9 provinces: Anhui, Chongqing, Guangdong, Hebei, Henan, Hubei, Jiangsu, Sichuan, and Zhejiang.
The Urban Migrant Survey was conducted in the following 15 cities, which are provincial capital cities or other major migrant receiving cities: Bengbu, Chengdu, Chongqing, Dongguan, Guangzhou, Hefei, Hangzhou, Luoyang, Nanjing, Ningbo, Shanghai, Shenzen, Wuhan, Wuxi, Zhengzhou.
The Urban Household Survey was conducted in 19 cities and includes the following additional cities to the Urban Migrant Survey: Anyang, Jiande, Leshan and Mianyang.
The RUMiC survey is designed to provide a longitudinal dataset covering a four-year time span, tracking respondents so long as they remain in the surveyed cities and villages. The Rural and Urban Household Surveys follow a normal tracking method used in any longitudinal surveys with subjects having permanent living addresses. In general, the attrition rate for these two populations is within the normal range. Between the first and the second waves, the attrition rate for the Rural Household Survey was 1% and for the Urban Household Survey was 5.7%. The attrition rates for these two samples increased between the second and the third waves due to the change in survey conductor, but they still remain in a low range.
The tracking for the Urban Migrant Survey, however, is more difficult. The pre-test results indicate that migrant workers on average stay in a city for around 3 years, and none who lived in a residential address stays for more than a year. To ensure the tracking result, the survey team recorded the individual migrants? work and home addresses and other contact details in the cities as well as their home villages. We also recorded the phone numbers of three close relatives or friends of each interviewee so that we could track them even if they and their households moved. In addition, the team designed a tracking incentive scheme of three lotteries each year, with prizes from 50 to 2000 Yuan. Despite these efforts, the attrition rate for the Urban Migrant Survey has been very high.
The survey does not track returning migrants due to high costs. Between the first and the second wave, partly due to the high mobility and partly due to the global financial crisis, the attrition rate for the Urban Migrant Survey was 64%. In the subsequent waves the attrition rate gradually came down with the second to the third wave attrition rate being 52% and the third to the fourth wave rate being 43%.
The RUMiC survey was part of the RUMiCI project, which included surveys conducted in Indonesia
Replication data for: Teacher Expectations Matter
No full textPapageorge, Nicholas W., Gershenson, Seth, and Kang, Kyung Min, (2020) “Teacher Expectations Matter.” Review of Economics and Statistics 102:2, 234–251
Replication data for: Macroeconomic Conditions When Young Shape Job Preferences for Life
No full textCotofan, Maria, Cassar, Lea, Dur, Robert, and Meier, Stephan, (2023) “Macroeconomic Conditions When Young Shape Job Preferences for Life.” Review of Economics and Statistics 105:2, 467–473