| Field | Before | After |
|---|---|---|
| Field Abstract | Before Identifying and alleviating constraints to improve productivity for small and medium enterprises (SMEs) is critical for increasing output and improving incomes in rural communities in low-resource settings. Yet little is known about the specific supply-chain bottlenecks that prevent business owners and entrepreneurs from expanding their operations. This research asks if lowering search costs along the supply chain decreases market frictions by improving small firms ability to source and sell goods in their local area. The proposed field experiment leverages the scale-up of an existing program where small firms can opt to list their sector, location, and phone number in a digital phone book accessible by anyone with a mobile phone. The results will inform researchers and policymakers about what types of technology can move the needle on a firms’ ability to invest in their businesses and improve their operations. | After Substantial information frictions along supply chains of small firms can generate bottlenecks which slow the dissemination of competitive terms of trade and other market information. This research investigates whether lowering search costs decreases information frictions and improves small firms' ability to source and sell goods in their local area. It leverages the scale-up of a digital phonebook application that effectively lowers the cost of accessing new business and customer networks. Participating small firms are split into a control and treatment group with two variations - 1) a business listing targeting input markets in urban areas, and 2) a business listing targeting customers in output markets in rural areas. The design allows for comparing the extent to which input or output business networks constrain business performance in rural markets and whether lowering the cost of initial contact improves firm productivity. |
| Field Last Published | Before September 16, 2019 02:08 PM | After December 15, 2019 08:49 PM |
| Field Primary Outcomes (End Points) | Before Number of supplier contacts, Number of customer contacts, Firms conducts business outside their local market, Firm engages in price search activities | After Number of supplier contacts, Number of customer contacts, Firms conducts business outside their local market |
| Field Primary Outcomes (Explanation) | Before The primary outcome variables concentrate on outcomes related to firm contact with suppliers and customers. During follow-up phone surveys, we will ask whether new suppliers and customers called or came to the storefront. Although treatments are designed to increase either upstream contacts or downstream contacts, these outcomes will be measured for all firms to allow comparison between treatment arms. The other primary outcome variables - conducting search outside their local market and engaging in price search - are designed to pick up changes in the geographic area over which the firm conducts its business. | After The primary outcome variables concentrate on outcomes related to firm contact with suppliers and customers. During follow-up phone surveys, we will ask whether new suppliers and customers called or came to the storefront. Although treatments are designed to increase either upstream contacts or downstream contacts, these outcomes will be measured for all firms to allow comparison between treatment arms. The other primary outcome variable - conducting business outside their local market - is designed to pick up changes in the geographic area over which the firm conducts its business. |
| Field Experimental Design (Public) | Before First, a sample of communities was drawn by selecting 20 medium-sized villages located between three large city hubs: Dodoma City, Singida City, and Manyoni town. Communities with a population above 3,000 people (per the 2012 Tanzanian census) were eligible. Qualifying communities were selected after stratifying on population and distance to the nearest city. After selecting communities, the research team traveled to each location and invited all businesses to enroll in the digital phone directory and conducted the baseline survey. Firms that agreed to participate became the baseline sample and were randomly divided in the control and two treatments at the individual level, after stratifying on firm sector, market size (number of firms per village), gender of the firm owner, and a measure of how much the firm preferred to have their business listing shown within their local market versus the city market (see PAP for a full explanation). | After First, a sample of communities was drawn by selecting 20 medium-sized villages located between three large city hubs: Dodoma City, Singida City, and Manyoni town. Communities with a population above 3,000 people (per the 2012 Tanzanian census) were eligible. Qualifying communities were selected after stratifying on population and distance to the nearest city. After selecting communities, the research team traveled to each location and invited all businesses to enroll in the digital phone directory and conducted the baseline survey. Firms that agreed to participate became the baseline sample and were randomly divided in the control and two treatments at the individual level, after stratifying on firm sector, village, gender of the firm owner, and a measure of how much the firm preferred to have their business listing shown within their local market versus the city market (see PAP for a full explanation). |
| Field Planned Number of Clusters | Before 497 firms offered to list business in directory, 413 uptake offer to participate | After 20 villages |
| Field Planned Number of Observations | Before 413 firms | After 500 firms |
| Field Sample size (or number of clusters) by treatment arms | Before Upstream treatment: 138 Downstream treatment: 138 Control: 137 | After Upstream treatment: 166 Downstream treatment: 166 Control: 168 |
| Field Power calculation: Minimum Detectable Effect Size for Main Outcomes | Before Power calculations are estimated assuming a level of 0.8 and setting size to .05. With a sample of 413 firms, and 138 per treatment arm, we are powered to pick up changes greater or equal to 0.16 standard deviations. For the first primary outcome (phone calls with upstream and downstream contacts), this translates to a minimum detectable effect size of .51 more phone calls, a 18% increase over the baseline mean of 2.84 phone calls. | After See pre-analysis plan |
| Field Additional Keyword(s) | Before Firm networks, Supply chains | After Firm networks, Supply chains, Geography of Markets |
| Field Public analysis plan | Before No | After Yes |
| Field Secondary Outcomes (End Points) | Before Changes in input and output prices of select goods, Sourcing costs efficiency, Bargaining activities, Responses to stock-outs, Marketing Activities, Business performance index | After Changes in input and output prices of select goods, Sourcing costs efficiency, Responses to stock-outs, Marketing Activities, Business performance index |
| Field Secondary Outcomes (Explanation) | Before Sourcing Efficiency: Firms’ upstream inputs sourcing activity will be used to construct a variable that measures the extent to which treated firms improve productivity in their input market. Bargaining activities measure the extent to which firms search for price and information that are useful for business decisions. Stock-outs measures whether customers request relevant goods that the firm does not have in stock. If stock-outs decrease as a result of treatment, it provides evidence that increasing network opportunities could improve availability of goods in local market areas. The business performance index will be a composite measure of sales, number of customers, number of workers, and hours worked. Input and output prices: Respondents will be asked to select three primary goods and asked to provide the price they paid for that good. Those items will then be stored and asked again during follow-up surveys in order to learn whether the firm sources or sells goods at different prices. | After Sourcing Efficiency: Firms’ upstream inputs sourcing activity will be used to construct a variable that measures the extent to which treated firms improve productivity in their input market. Stock-outs measures whether customers request relevant goods that the firm does not have in stock. If stock-outs decrease as a result of treatment, it provides evidence that increasing network opportunities could improve availability of goods in local market areas. The business performance index will be a composite measure of sales, number of customers, number of workers, and hours worked. Input and output prices: Respondents will be asked to select three primary goods and asked to provide the price they paid for that good. Those items will then be stored and asked again during follow-up surveys in order to learn whether the firm sources or sells goods at different prices. |
| Field | Before | After |
|---|---|---|
| Field Document | Before |
After
PreAP_eKichabi.pdf
MD5:
ddd73dd8f532e6112e701622c846231a
SHA1:
fc7b4b1ac876c6b7ec4a6b5bfffa6d96e20c08d9
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| Field Title | Before | After eKichabi Pre-Analysis Plan |