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DESIGNING AN INDUSTRIAL POLICY FOR DEVELOPING COUNTRIES: A NEW APPROACH
Last registered on August 06, 2018

Pre-Trial

Trial Information
General Information
Title
DESIGNING AN INDUSTRIAL POLICY FOR DEVELOPING COUNTRIES: A NEW APPROACH
RCT ID
AEARCTR-0003215
Initial registration date
August 04, 2018
Last updated
August 06, 2018 3:56 AM EDT
Location(s)
Primary Investigator
Affiliation
Shahid Beheshti University
Other Primary Investigator(s)
Additional Trial Information
Status
Completed
Start date
2016-04-08
End date
2018-08-04
Secondary IDs
Abstract
In this study, the prevalent methodology for design of the industrial policy for developing country was critically assessed, and it was shown that the mechanism and content of classical method is fundamentally contradictory to the goals and components of the endogenous growth theories. This study, by proposing a new approach, along settling Schumpeter's economic growth theory as a policy framework, designed the process of entering, analyzing and processing data as the mechanism of the industrial policy in order to provide "theoretical consistency" and "technical and Statistical requirements" for targeting the growth stimulant factor effectively.
External Link(s)
Registration Citation
Citation
Haeri, Ali. 2018. "DESIGNING AN INDUSTRIAL POLICY FOR DEVELOPING COUNTRIES: A NEW APPROACH." AEA RCT Registry. August 06. https://doi.org/10.1257/rct.3215-1.0.
Former Citation
Haeri, Ali. 2018. "DESIGNING AN INDUSTRIAL POLICY FOR DEVELOPING COUNTRIES: A NEW APPROACH." AEA RCT Registry. August 06. http://www.socialscienceregistry.org/trials/3215/history/32691.
Experimental Details
Interventions
Intervention(s)
Corresponding Author
Intervention Start Date
2016-04-09
Intervention End Date
2018-08-03
Primary Outcomes
Primary Outcomes (end points)
no interest
Primary Outcomes (explanation)
no relevant data
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
industry
Experimental Design Details
new approach
Randomization Method
randomization done in office by a computer
Randomization Unit
clusters
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
200
Sample size: planned number of observations
10000
Sample size (or number of clusters) by treatment arms
50
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
IRB Approval Date
IRB Approval Number
Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
No
Is data collection complete?
Data Publication
Data Publication
Is public data available?
No
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)
REPORTS & OTHER MATERIALS