Local and Regional Procurement Learning Alliance 9. Market Data DATA QUALITY CONTROL.

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Local and Regional Procurement Learning Alliance 9. Market Data DATA QUALITY CONTROL

Before going to the field: answer these questions What days of the week or month do your target markets operate? What are the characteristics of the commodities to be monitored? Who are retailers? Who are wholesalers? How are they different? How should an enumerator select a trader to interview? 2

How do you use a scale to weigh commodity? When interviewing retailers, at what volumes should prices be collected? When interviewing wholesalers, at what volumes should prices be collected? When interviewing wholesalers who also have a retail business, should both sets of prices be collected? How frequently should prices be collected? 3 Before going to the field: answer these questions cont.

When are the market’s busy times? –Visit during slower times What if a trader does not sell a particular commodity or does sell it but is unable to provide a current price? What if more than one trader is unable to provide a price for a particular commodity type or variety? What if there are not enough wholesalers or retailers in a community? 4 Before going to the field: answer these questions cont.

What if prices are reached through bargaining? –Ask for the trader’s “average” or “normal” price When returning to a market, who should be interviewed? If a trader formerly interviewed is not available or is unwilling, who should an enumerator interview? 5 Before going to the field: answer these questions cont.

Before leaving the field: check your data Are there any missing values? Are any responses unclear or vague? Optional for each country office: –Check for consistency of commodity prices within each market Examine wholesale prices separately from retail prices After collecting price information for a commodity from the wholesalers, convert each price into the same per-unit price If a single per unit price is an outlier, verify that that reported price is correct –Rule of thumb: single outlier price is two or three times larger or smaller than the other prices Do the same for retailers 6

Optional: Before leaving the field: convert each price into the same unit price, by trader type 7 Wholesaler conversions Retailer conversions Market A Standard Unit Number of units to reach at least 2kgs Weight on the scale Price / standard unit Local rice price /kg Trader 1kg2250 Trader 2cup Trader 3cup Trader 4cup Trader 5can Average69

Optional: Before leaving the field: what may be causing data inconsistencies? If a single per unit price is two or three times larger or smaller than the other prices, enumerator should verify that that reported price is correct –What could be causing these differences? Rule out sources of error before leaving the field Making life easy for enumerators / field staff –Field staff may need calculators to check data –Data check sheet for listing the converted prices will make comparisons easier 8

During data entry: check your data Enter data into the database (to be developed) Check for missing values. If any values are missing, ask the enumerators why these prices were not available Enter prices into the appropriate spreadsheet or database and graph each commodity’s prices across markets over time Graph each market’s prices for all commodity monitored in this market; check for irregularities 9

During data entry: check your data 10