The Returns to Investments in Equipment Upgrades at Vocational Education Schools: Evidence from a RCT in Mongolia

Last registered on March 30, 2015

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Pre-Trial

Trial Information

General Information

Title

The Returns to Investments in Equipment Upgrades at Vocational Education Schools: Evidence from a RCT in Mongolia

RCT ID

AEARCTR-0000155

Initial registration date

March 30, 2015

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published

March 30, 2015, 5:38 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Country

Mongolia

Region

Primary Investigator

Name

Leigh Linden

Affiliation

The University of Texas at Austin

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Other Primary Investigator(s)

PI Name

Daniel Rubenson

PI Affiliation

Ryerson University

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PI Name

Shing-Yi Wang

PI Affiliation

Wharton School, University of Pennsylvania

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PI Name

Erica Field

PI Affiliation

Duke University

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PI Name

Leigh Linden

PI Affiliation

University of Texas at Austin

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Additional Trial Information

Status

On going

Start date

2010-05-06

End date

2016-01-31

Keywords

Education

Additional Keywords

Vocational Education, Tertiary Education, Youth Employment

JEL code(s)

C93, I21, I38

Secondary IDs

Abstract

Do investments in equipment upgrades at Vocational and Technical Education Training (TVET) schools increase the wages and employability of poor Mongolians? This study will evaluate the incremental impact of school equipment upgrades on both academic and labor-market outcomes. We hypothesize that being assigned to study with upgraded equipment will cause students to be more likely to train with improved equipment. We hypothesize that exposure to more current equipment will improve their factual understanding of the trade and familiarize the students with the tools actually used by employers. Employers should then find students more productive than they otherwise would, making it more likely that students will be able to find employment and increasing the wages that employers are willing to pay them. To identify these effects, we worked with a select set of TVET schools in Mongolia to conduct admissions lotteries in three admission years, 2010, 2011, and 2012. Baseline data was collected at time of admission application and follow-up data will be analyzed to assess the impact of TVET training with improved equipment on labor market outcomes.

External Link(s)

The Millennium Challenge Corporation's Mongolia Impact Evaluation Page

Registration Citation

Citation

, et al. 2015. "The Returns to Investments in Equipment Upgrades at Vocational Education Schools: Evidence from a RCT in Mongolia." AEA RCT Registry. March 30. https://doi.org/10.1257/rct.155

Former Citation

, et al. 2015. "The Returns to Investments in Equipment Upgrades at Vocational Education Schools: Evidence from a RCT in Mongolia." AEA RCT Registry. March 30. https://www.socialscienceregistry.org/trials/155/history/3920

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Experimental Details

Interventions

Intervention(s)

We evaluate investments into equipment upgrades at Technical and Vocational Education Training (TVET) schools in Mongolia, a part of the Vocational Education Training Project sponsored by the Millennium Challenge Corporation (MCC) and designed to address the gaps in Mongolia’s vocational education system. The project seeks to increase the wages of poor Mongolians by improving their technical skills and productivity to meet labor market demand in key industries (including, among others, construction, mining, electronics, mechanics, and transport). More than half of MCC’s investment into the Mongolian TVET sector was spent on upgrading equipment and constructing and rehabilitating workshops. The upgrades of 19 categories of equipment in the ten schools participating in this study were completed in August 2013, ultimately affecting 21 trades.

We hypothesize that a school receiving the equipment upgrades will cause students in affected trades to be more likely to train with improved equipment. This experience with modern, relevant equipment will improve their factual understanding of the trade and familiarize the students with the tools used by employers. Employers should then find students more productive than they otherwise would, making it more likely that students will be able to find employment and increasing the wages that employers are willing to pay them.

Intervention Start Date

2010-09-01

Intervention End Date

2016-01-31

Primary Outcomes

Primary Outcomes (end points)

Key outcomes include earnings, employment, type of employment, and graduates' trade-specific skills.

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

This study will primarily evaluate the incremental impact of school equipment upgrades on both academic and labor-market outcomes. Comparable control and treatment groups necessary to estimate the effect of TVET training was created through randomized admissions process in three consecutive academic years. Out of a pool of ‘qualified’ applicants, students were chosen at random to gain admittance to the school and randomly assigned to study specific trades. Surveys were administered to the entire pool of applicants at the time of the application, including a standardized general knowledge test to measure skill levels and academic performance. Shortly after graduation, a follow-up survey will be administered to collect information on labor-market outcomes, including wages and hours worked. Students will also complete standardized trade tests that measure knowledge and skills in specific trades. This follow-up survey will continue annually for three years.

Experimental Design Details

Randomization Method

Randomization done by computer

Randomization Unit

Randomization occurred at the level of the individual applicant to the TVET schools.

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

N/A

Sample size: planned number of observations

11,000 Applicants

Sample size (or number of clusters) by treatment arms

2,886 applicants were assigned to study at schools in trades that received upgraded equipment.
8,126 applicants were not assigned to either a trade or school that received upgraded equipment.

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

MDE's for Monthly Exposure to Improved Equipment: Upper bound: 0.01 std. deviations for Skills Test scores; 0.42% Employment change; 1.7 USD monthly income change Lower Bound: 0.0056 Std. deviations for skills test scores; 0.24% Employment change and 0.94 USD monthly income change

Supporting Documents and Materials

IRB