in quality and can be relatively easily arbitraged across time and location (stored). The idea is to analyze prices of goods whose characteristics make the possibility of the existence of efficient markets a more plausible one.

The set of goods selected for the analysis intends to comply with these requirements (see Table 2, above). A total of 54 specific goods were selected and are studied from January 2010 to December 2015, meaning that there are 144 periods of data gatherings. The database has over 1,770,000 observations and comprises prices from 3,386 retail stores located in each of the 46 cities.

The selected specifics are homogenous: varieties. There few, negligible; differences in quality or other characteristics (such as brand) that are low and relatively easy to observe in the data; and presentation/packaging is fairly standard. A good number of these are perishable goods—fruits, vegetables, meat, and some varieties of bread and corn tortilla—with no brand, or packaging and sold in bulk. The non-perishables such as bottled water, soda, sugar, salt and cement are classified according to size, variety and package, while brand is removed. We clarify that, in order for two specifics of different brands to be considered the same, the brands had to be “similar” in terms of market coverage (i.e. they had to be quite common nationally, regionally or within a city) and in price levels.

INEGI has deep coverage of the goods selected at the city level. In most cases, there are several price quotes within a city at a certain time period. This is an important requirement for the data when calculating market efficiency indicators, especially dispersion.

More importantly, the sample of goods is highly representative in the basket of consumption of Mexican households belonging to the bottom 40 percent of the income distribution. They represent 29 percent of consumption expenditure of such households. This selection criterion left us be confident that the goods we follow share two important properties: 1) The markets of these goods are, with all probability, thick, given their high level of expenditure; and 2) These goods are indeed “meaningful” to households, especially to the poorest ones who are the most likely to be affected by changes in prices.

The price data required cleaning. In some cases, this was due to missing prices for certain specifics, for which sometimes INEGI attributed either the price of a “similar” specific within the same store, the price of the missing specific from a nearby store, or an average price within a city or region (what INEGI calls precios imputados—imputed prices). Other cases related to misspellings and errors in data collection such as the misplacing of decimal points, prices not standardized and other (undecipherable) errors. When errors were clearly identifiable, they were corrected. Price quotes were dropped when these were precios imputados or the price levels were considered as outliers. We defined outliers as prices that suddenly changed and were below/above three standard deviations according to a 3-month moving window or those whose level was suddenly below/above three standard deviations of its price distribution nationally.

# International prices

In addition to INEGI INPC data, other sources were used to gather data required to both calculate indicators and to use as controls for regressions. International prices of goods were required to estimate pass-through. International prices were not available for all commodities, especially for non-perishables, such as cement, soda or water that can be 11