Learning and Educational Achievement in Punjab Schools (LEAPS) - Master Data 2003-2006

Pakistan, 2003 - 2006

Reference ID

PAK_2006_LEAPSM_v01_M

Producer(s)

Tahir Andrabi (Pomona College), Jishnu Das and Tara Viswanath (World Bank), Asim Ijaz Khwaja and Tristan Zajonc (Harvard University)

Collection(s)

Development Research Microdata

Metadata

Documentation in PDF DDI/XML JSON

Study website

Created on

Apr 11, 2011

Last modified

Dec 06, 2016

Page views

43535

Downloads

18380

Identification

Survey ID number

PAK_2006_LEAPSM_v01_M

Title

Learning and Educational Achievement in Punjab Schools (LEAPS) - Master Data 2003-2006

Country/Economy

Name	Country code
Pakistan	PAK

Series Information

LEAPS surveys were conducted in 2003, 2004 and 2006

Abstract

The Master datasets comprise of four datasets: on children, schools, teachers and households. These master datasets contain key variables and identifiers which will allow users of the data to determine the progression of sample sizes and attrition of children, households, schools and teachers across the four years of the LEAPS panel data.

The children dataset contains round-by-round status of children's grades, enrollment, promotion etc. It also has variables indicating the panel child belongs to (the first panel being grade 3 children LEAPS started following in 2003, and the second one being 3rd graders followed starting in 2005 i.e. round 3 of the survey) as well as whether child was randomly selected for child questionnaire in class.
The school dataset contains information such as school type, survey status, construction date. Note that there is only one schoolid variable and it is constant across all rounds. To capture the fact that there is merging of some schools going on across the rounds, refer to the school_merged_into and school_merged_with variables. The school_merged_into variable only exists for the small schools that merged into a larger school whereas the school_merged_with variable exists for the larger schools that the smaller schools merged in to.
The teachers dataset contains information such as their round-by-round school, teaching status.
The household dataset contains a Mauza indicator, and a variable on whether the household was surveyed in a particular round.

Version

Version Description

Public Release Version 1.0

Scope

Keywords

Education Enrollmemt Pakistan Rural Educational Achievement Test Scores

Coverage

Geographic Coverage

Rural Punjab, Pakistan

Producers and sponsors

Primary investigators

Name
Tahir Andrabi (Pomona College), Jishnu Das and Tara Viswanath (World Bank), Asim Ijaz Khwaja and Tristan Zajonc (Harvard University)

Sampling

Sampling Procedure

The sample comprises 112 villages in 3 districts of Punjab-Attock, Faisalabad and Rahim Yar Khan. The districts represent an accepted stratification of the province into North (Attock), Central (Faisalabad) and South (Rahim Yar Khan). The 112 villages in these districts were chosen randomly from the list of all villages with an existing private school. This allows us to look at differences between private and public schools in the same village. Although these villages are thus bigger and richer than average villages in these districts, we believe this is a forward-looking strategy and the insights earned here will soon be applicable to a significant fraction of all villages in the country.

Deviations from the Sample Design

None

Response Rate

The attrition has been remarkably small, averaging 3-4 percent in each year.

Data collection

Dates of Data Collection

Start	End
2003	2006

Time Method

2003-2007

Supervision

Tracking Children: In 2004 we tested 12,000 children in 838 public and private schools in Grade 3 and re-tested them in Grades 4 (2005) and 5 (2006). In 2006, we also included Grade 3 children, increasing the total number of children tested to
25,000. These children all need to be tracked through the year to find out where they are the next year. The table below shows for instance, the status of child-tracking as they moved from Grade 3 to Grade 4. In the transition children could (a) drop-out (b) remain in the same school and be promoted; (c) remain in the same school and not be promoted; (d) switch schools within the village and be promoted (in which case they would be tested in another school) and be promoted; (e) switch to schools within the village and not be promoted and (f) switch to schools outside the village or leave the village all together. Although close to 1800 children out of 12,000 were no longer in the same class-school combination that they would have been if they did not switch schools and were promoted, we were able to determine the status of all except 500. In one previous study, authors could track only 10 percent of the children compared to our rate of above 95 percent.

Surveying Households: We have now created a longitudinal dataset of 1800 households across the 3 years, and in each of the years there are close to 750 children on whom we also have information on learning from the school testing exercise. This is the first database in low-income countries that combines detailed household information (including consumption aggregates) with school-level inputs and learning.

Data Access

Access conditions

In order to access the data, you will be required to register. Registration is a simple one-step process and is only designed to allow us to keep a track of the users of this data.

Citation requirements

Use of the dataset must be acknowledged using a citation which would include:

the Identification of the Primary Investigator
the title of the survey (including acronym and year of implementation)
the survey reference number
the source and date of download

Deposit requirements

In order to keep our database uptodate, we request that you provide us with a citation to the work you produce using the LEAPS data.

Availability Status

The data from year 2 will be available by December 2007.

Disclaimer and copyrights

Disclaimer

To the best of our knowledge and ability, the data has been purged of identifying variables and errors of coding.

The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.

Metadata production

DDI Document ID

DDI_PAK_2006_LEAPSM_v01_M

Date of Metadata Production

2006-07-21

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