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E-Commerce Integration and Economic Development: Evidence from China

Last registered on October 06, 2016
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Pre-Trial

Trial Information

General Information

Title
E-Commerce Integration and Household Welfare: Evidence from Taobao's 100 Thousand Villages Project
RCT ID
AEARCTR-0001582
Initial registration date
October 06, 2016

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
October 06, 2016, 5:12 PM EDT

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

Locations

Country
China
Region
Anhui, Henan, Guizhou, Yunnan

Primary Investigator

Name
Benjamin Faber
Affiliation
Department of Economics, UC Berkeley
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Other Primary Investigator(s)

PI Name
Lizhi Liu
PI Affiliation
Department of Political Science, Stanford University
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PI Name
Yizhen Gu
PI Affiliation
Institute of Economic and Social Research, Jinan University
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PI Name
Victor Couture
PI Affiliation
Haas School of Business, UC Berkeley
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Additional Trial Information

Status
In development
Start date
2015-12-21
End date
2017-12-31
Keywords
Welfare
Additional Keywords
Trade integration, internet, e-commerce, welfare gains
JEL code(s)
Secondary IDs
Abstract
Since 2000, more than half of China's population have been connected to and by the internet. Over this period, the number of Chinese buying and/or selling products online has grown from practically zero to more than 400 million in 2015, surpassing the US as the largest online retail market. Despite this trajectory, we currently have limited empirical evidence on the economic consequences of e-commerce as a channel of market integration. This paper brings to bear a new collection of microdata in combination with a randomized controlled trial (RCT) that we implement in collaboration with the Chinese internet firm Alibaba. Alibaba owns the dominant Chinese e-commerce platform Taobao through which consumers and producers can buy and sell products of all kinds. Taobao's 100 Thousand Villages Project (HTVP) aims to build the necessary transport logistics to ship products to and sell products from 100,000 villages that were previously unconnected to e-commerce. As part of this operation, Alibaba installs a Taobao terminal at a central village store where households can buy and sell products through the store manager's Taobao account. We were given authorization to randomly select control villages in several Chinese counties from a list of candidates that had been extended by the number of control villages for the purpose of this research. We collect household and store price survey data for treatment and control vilalges, and complement these data with online transaction records from Taobao. We plan to use this empirical setting to answer three central questions: i) what are the household economic gains from e-commerce integration?, ii) what are the channels underlying these effects?, and iii) what is the distribution of the gains from e-commerce across different groups of households?
External Link(s)

Registration Citation

Citation
Couture, Victor et al. 2016. "E-Commerce Integration and Household Welfare: Evidence from Taobao's 100 Thousand Villages Project." AEA RCT Registry. October 06. https://doi.org/10.1257/rct.1582-1.0
Former Citation
Couture, Victor et al. 2016. "E-Commerce Integration and Household Welfare: Evidence from Taobao's 100 Thousand Villages Project." AEA RCT Registry. October 06. https://www.socialscienceregistry.org/trials/1582/history/11128
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Taobao's 100 Thousand Villages Project aims to build the necessary logistics to ship products to and sell products from villages that were previously unconnected to e-commerce. The objective is to bring the transport costs of e-commerce related shipments to and from the participating villages to the same level as for the urban parts of the county in question. As part of this operation, Alibaba builds warehouses, subsidizes transport fares to and from the villages, and installs a Taobao terminal at a central village store where households can buy and sell products through the store manager's Taobao account. Households can pay or be paid in cash at the store upon arrival or pickup of the products without the need for online payments.
Intervention Start Date
2016-01-14
Intervention End Date
2016-10-31

Primary Outcomes

Primary Outcomes (end points)
Local retail prices, household incomes, household consumption expenditure shares on e-commerce across different product groups. All these serve to inform the measurement of changes in household real incomes.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The unit of randomization is the village. For each county, we obtain a list of candidates that had been extended by 5 promising village candidates that would have not been part of the list in absence of our research. The two main factors determining the village selection within a county from Taobao’s operational perspective are i) a sufficient level of local population, and ii) the presence of a capable store applicant (as measured by test score of applicant). Upon receipt of this extended list of village candidates for each county, we randomly select 5 control villages and 7-8 treatment villages from the list of candidates for each county. The remaining villages on the list also receive Taobao terminals as planned. We stratify treatment and control villages along four dimensions: pre-existing availability of commercial package delivery, local store applicants’ test scores, village population, and the ratio of non-agricultural employment over the local population. After obtaining the candidate lists, we have on average 2-3 weeks to run the randomization and send in enumerators for data collection in 5 control villages and the 7-8 treatment villages before the terminal installations take place and e-commerce begins in the treatment villages.
Experimental Design Details
Randomization Method
Randomization done in office by computer.
Randomization Unit
The unit of randomization is the village.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
100 villages
Sample size: planned number of observations
2800 households, 11500 local price quotes per round.
Sample size (or number of clusters) by treatment arms
40 control villages, 60 treatment villages.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Office for the Protection of Human Subjects, UC Berkeley
IRB Approval Date
2016-04-15
IRB Approval Number
Protocol No: 2015-09-7944
Analysis Plan

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Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
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