metadata: authors: 0: author: Iacovone,Leonardo
1: author: Gonzalez,Alvaro S.
2: author: Sanchez Bayardo,Luis Fernando
count: Mexico
docna: 0: docna: Micro-level analysis of Mexican retail
            markets and their response to changes in market structure
            and competition policies
docty: Policy Research Working Paper
subtopic: Hydrology,International Trade and Trade Rules,Food Security,Macroeconomic Management,Transport Services
teratopic: Private Sector Development,Science and Technology Development,Industry,International Economics and Trade
abstracts: cdata!: This paper develops the following price
            indicators to measure the relative efficiency (functioning)
            of markets: (a) price dispersion, (b) price volatility, and
            (c) price transmission (speed, completeness, and symmetry).
            The paper uses these indicators to study trends and
            conditions of the outlet level in retail prices for common
            commodities sold throughout Mexico. The analysis examines
            price patterns for each indicator across commodities,
            regions, and time. The descriptive results indicate that
            although there is (expected) heterogeneity in the behavior
            of these indicators across commodities, location variables
            explain the most variation in the indicators. There are
            clear and persistent regional- and commodity-specific
            effects. Thus, the study concludes that Mexico is not one,
            well-integrated national market. The study tested whether
            changes in these indicators (increased efficiency) have the
            expected correlation with measures affecting the functioning
            of markets. It considered changes in competition and entry
            of large retail stores in the local retail market. These
            changes affect market efficiency in the way theory would
            predict. The results suggest that these indicators are good
            measures of the relative efficiency (functioning) of
            markets. The findings also suggest that efforts to monitor
            markets using these indicators may be useful. For example,
            for policy makers who are concerned about the distributional
            effects of liberalizing trade, the indicators may predict
            where price impacts will be felt the most and by whom. In
            addition, the indicators provide preliminary information
            about relative competition levels, which may be helpful in
            saving the time and effort of the competition authorities
            and possibly making them more effective.
geo_reg_key: 119228,517191
repnme: repnme: Micro-level analysis of Mexican retail
            markets and their response to changes in market structure
            and competition policies
display_title: Micro-level analysis of Mexican
            retail markets and their response to changes in market
            structure and competition policies
listing_relative_url: /research/2018/01/29473545/micro-level-analysis-mexican-retail-markets-response-changes-market-structure-competition-policies
topicv3: Price Volatility m1326059 1150,Agriculture and Food Security m1326205 435,Water m1326522 137,Transport m1326661 135,Trade m1326924 698
publishtoextweb_dt: 2018-01-08T00:00:00Z
historic_topic: Private Sector Development,Science and Technology Development,Industry,International Economics and Trade
no_of_pages: 45
author_keys: 0: author_key: 900307
1: author_key: 793227
2: author_key: 1366765
model_extractions: WPS8294 Policy Research Working Paper 8294 Micro-Level Analysis of Mexican Retail Markets and Their Response to Changes in Market Structure and Competition Policies _Luis Fernando Sanchez-Bayardo Alvaro Gonzalez Leonardo Iacovone_ Jobs Cross Cutting Solution Area January 2018
Policy Research Working Paper 8294

# **Abstract**

This paper develops the following price indicators to measure the relative efficiency (functioning) of markets: (a) price dispersion, (b) price volatility, and (c) price transmission (speed, completeness, and symmetry). The paper uses these indicators to study trends and conditions of the outlet level in retail prices for common commodities sold throughout Mexico. The analysis examines price patterns for each indicator across commodities, regions, and time. The descriptive results indicate that although there is (expected) heterogeneity in the behavior of these indicators across commodities, location variables explain the most variation in the indicators. There are clear and persistent regional- and commodity-specific effects. Thus, the study concludes that Mexico is not one, well-integrated national market. The study tested whether changes in these indicators (increased efficiency) have the expected correlation with measures affecting the functioning of markets. It considered changes in competition and entry of large retail stores in the local retail market. These changes affect market efficiency in the way theory would predict. The results suggest that these indicators are good measures of the relative efficiency (functioning) of markets. The findings also suggest that efforts to monitor markets using these indicators may be useful. For example, for policy makers who are concerned about the distributional effects of liberalizing trade, the indicators may predict where price impacts will be felt the most and by whom. In addition, the indicators provide preliminary information about relative competition levels, which may be helpful in saving the time and effort of the competition authorities and possibly making them more effective.

This paper is a product of the Jobs Cross Cutting Solution Area. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at agonzalez4@ worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
Micro-Level Analysis of Mexican Retail Markets and Their Response to Changes in Market Structure and Competition Policies Luis Fernando Sanchez-Bayardo, Alvaro Gonzalez and Leonardo Iacovone

**Keywords:** prices, competition, entry, integration JEL Classification Codes: L10, L11, L81, F15, F61
# TABLE OF CONTENTS

|Introduction .......................................................................................................................... 1|
|---|
|Literature review ................................................................................................................. 3|
|Data ....................................................................................................................................... 6|
|Empirical strategy .............................................................................................................. 13|
|Descriptive statistics .......................................................................................................... 18|
|Regression results .............................................................................................................. 27|
|Conclusions ......................................................................................................................... 34|
|Appendix ............................................................................................................................. 36|
|References ........................................................................................................................... 37|
# INTRODUCTION

The choice to transact in a market—as a buyer, seller or intermediary—depends on price signals. Supposedly, when markets function well they send the ‘right’ price signals. Price levels, movements and trends represent the relative levels, changes and trends in the surplus and scarcity of goods and changes in the inherent value of these goods to both seller and buyer. Under these conditions, when parties transact, exchange benefits all.

But markets may not function well and send the ‘right’ prices. Some markets may exhibit persistent and relatively higher price volatility, may be less well integrated to international and national markets and indicate relatively attenuated capacity to arbitrage across time and space. Most importantly, the relative poor performance of some markets may not be random nor transitory. In the price data from Mexico examined for this study, there are distinct spatial and temporal patterns that one would expect market forces to address. Ceteris paribus, markets function to attenuate heterogeneity in price levels, changes and trends. There was a lot of persistent heterogeneity in these price data.

The motivation for this research was to identify and understand what prices, when and in which markets do not behave as theory would predict. To identify and comprehend the function of markets and price trends and conditions, this research focused on retail markets for perishable and non-perishable consumables of relatively homogeneous quality across Mexico.

This study looks at three dimensions of market efficiency; namely, price dispersion, passthrough of costs to prices and price volatility. With respect to price dispersion, price variations across physical space are expected not to be sizeable or persistent when markets work efficiently and market agents face stiff price competition. Regarding pass-through, in efficient markets a change in costs of inputs will be fully reflected (passed through completely) in the prices of commodities that use those inputs with minimal delay. In addition, when input costs go up, prices will go up as quickly and as completely as when input costs go down —this is a symmetry condition of pass-through of competitive and efficient markets.

Out of three proposed dimensions of market efficiency, volatility may be the least obvious dimension. However, volatility is indirectly related to efficiency. A benchmark on how much volatility is expected in an efficient market can be inferred. In well-functioning markets, volatility would solely be a function of the fundamentals of demand and supply. Because higher volatility introduces uncertainty, it increases the chances of buyer and seller error and it is something that both seller and buyer may be interested in reducing.<sup>1</sup> In addition, higher volatility may introduce temporally missing markets, especially when information is perfect—buyers delay purchases when they know prices will go down and sellers withdraw

> 1 The error is based on buying when prices may go down or selling when prices may go up in the next period. Some may object to categorizing this as an error. Admittedly, this sounds a lot like timing the market and this can only be done, without error, in hindsight (ex post). However, the error is not that unless a buyer or sellers can buy or sell at a better price, they make an error. The point is rather that in more volatile markets, using an average price as a representation of the likely market price, is a poorer heuristic at any period in time than in a less volatile market. When the average is a poorer heuristic, this means that the buyer or seller may pay too high or sell too low, respectively, than would otherwise be the case. This is what is meant here as an error.

1
goods when they know prices will go up.<sup>2</sup> In sum, higher price volatility indicates that a market will have to assume costs to overcome it. For that reason, higher volatility is assumed to be less efficient than lower volatility.

As already explained, the functioning of markets in this study refers to the comparison of the behavior of prices based on the following three dimensions: dispersion, volatility and passthrough. The study follows on and is informed by a pilot study in Nigeria. The results of that pilot study showed the following:

- Substantial heterogeneity in the dispersion, volatility and pass-through of markets across time and location for well-specified, homogenous commodities;<sup>3</sup> and

- This heterogeneity was robust across time and displayed distinct geographical and commodity-linked patterns.<sup>4</sup>

The results of the Nigeria study were preliminary and not published because the price data were of substantially poorer quality than price data available from Mexico. That said, we find similar results for Mexico.

In addition to identifying and understanding how well markets function across Mexico, we use these same indicators of market efficiency to determine how markets respond to changes in market structure and competition policies. Following Iacovone et al. (2011), this study expands on identifying the economic effects of a large retailer’s entry into Mexico. More specifically, instead of looking at the entry’s effect on manufacturing, this study examines the effect of entry on the performance of markets in locations near and far from the physical location of new stores. For the US, Fishman (2006) provides insight on the effects of WalMart on local markets. Driven mostly by constant reductions in transportation and production costs, Wal-Mart usually offers goods at lower prices than their competitors, in turn forcing the rest of retailers to drop their prices. Atkin et al. (2015) find similar results in prices for Mexico. Indeed, this study finds that a large retailer’s entry improves the functioning of markets as we have defined them. All things being equal, markets more immediately and directly affected from the entry of this large retailer function more efficiently after entry than those less affected.

Also, this research exploits the existing information on competition in Mexico to analyze the effects of anticompetitive practices on the functioning of markets. Using the documents published by the Mexican competition agency, COFECE, on investigations, opinions and resolutions regarding the existence of anticompetitive activities in industries and regions across time, a database is assembled to identify markets with distortions in competition and use these data as a control when evaluating the functioning of markets. It is shown that markets where anticompetitive practices are present behave less efficiently when no regulator acts to correct such inefficiencies.

The next section contains a literature review on the indicators of market efficiency used. The empirical strategy proposed to estimate the dimensions of efficiency of markets is discussed

> 2 The assumption is that the price falls below cost since price was set competitively—at zero economic profit.

> 3 White and yellow maize, local and imported rice, sorghum, cement and bottled water.

> 4 After controlling for physical isolation, proximity to international borders, economic density, competition, proximity to production of the commodity in question and broad measures of poverty.

2
as well as the definition of market efficiency. Following this, the results are provided. The final section presents conclusions and policy recommendations.

# LITERATURE REVIEW

This review of the literature on price dispersion, price volatility and price transmission is not meant to include the vast existing literature.

# Price dispersion

Price dispersion refers to the existence of more than one price for the exact same commodity at the exact same time, across different, nearby locations (Eckard, 2004). The existence of price dispersion implies that markets may not be completely efficient. In markets with high levels of competition, when prices differ across locations, unexploited arbitrage opportunities exist. Arbitrage would force long-run price differences to cover transaction costs, and the ‘Law of One Price’ (LOP) would generally hold. However, studies indicate that there are persistent deviations from LOP across cities within the same country. For example, even for narrowlydefined commodities, Ardeni (1989) finds that LOP does not hold. Trade costs are detected in domestic markets as well.

Trade costs are the most common explanation for violations to the Law of One Price (Crucini et al., 2005; Goyal, 2010; Lee, 2010; Blomberg and Engel, 2012). These costs include handling, marketing, breakage, stealing, spoilage, etc. (Crucini et al., 2005; Lee, 2010). Portugal-Pérez and Wilson (2008) and Atkin and Donaldson (2014) find that other market frictions limit the transmission of price signals and prohibit market arbitrage in African economies and lead to variation in prices for the same commodity.

In addition to trade, arbitrage and other transaction costs, Stigler (1961) argued that information is costly for buyers and this leads to price dispersion as well. He provided the first model of buyer’s imperfect information and price dispersion that others developed further (Salop and Stiglitz, 1977; Pratt, et al., 1979; Salop, 1979; Varian, 1980; Burdett and Judd, 1983; Stahl, 1989). These models show that many prices can exist and persist in equilibrium because it may be too costly for buyers to identify exactly which sellers, in a market with many sellers, are offering the lowest price. Some sellers benefit from this limited ignorance and can charge a higher price than others.

Theory on the importance of information for price convergence is supported by empirical evidence. Parker et al. (2013) look at grain price information in India acquired via mass text messages and find that price dispersion during an unanticipated short-term ban on mass text messages increased. Goyal (2010) estimates the impact of soy bean farmers having access to wholesale price information (via Internet kiosks and postings at warehouses) in India and finds that average prices rise and price dispersion decreases. A long-standing empirical literature documents considerable commodity price variability across space, especially in developing countries, with various empirical tests of market integration suggesting significant and puzzling forgone arbitrage opportunities (Fackler and Goodwin, 2001). Using variations in geographic coverage and rollout of mobile phone services, two studies found that price dispersion reduces dramatically for staple commodities, with bigger effects for fish in India (Jensen, 2007) than for grains in Niger (Aker, 2010).

3
Institutions seem to matter as well in the existence of price dispersions. A study by Gluschenko (2011) examines convergence to one price across the Russian Federation’s heterogeneous regions. He finds that markets with better institutions are more integrated, converging to a narrower band of prices for the same commodity, than regions where reforms have yet to take hold and market function is hampered by government interference, regulations and corruption. Blomberg and Engel (2012) find that price dispersion across Iraqi cities decreased during ‘the surge’, an increase in military presence, for a wide range of products. McCann (2012) shows that incidence of violence in Somalia augmented the bilateral price dispersion between Somali cities. But this might simply reflect increased transportation or trade costs as a reduction in military presence has an impact on illegal bribes (Olken and Barron 2009).

Cross-sectional variation in market power can also lead to different prices in what may seem to be the same market. Markets might, for example, not be large enough to support enough trade for perfect competition and exhibit a monopoly or oligopoly structure (Abbott, 1994; Bresnahan and Reiss, 1991; Shepard, 1991; and Stewart and Davis, 2005). But even in large markets, there may be enough market power through segmentation that some price dispersion may exist. For example, Çağlayan et al. (2012) explain the persistent deviation across shops in Istanbul by the presence of monopoly power for shops located within residential areas, where customers shop when they arrive home from work.

# Price volatility

From the perspective of the consumer, higher price volatility is associated to uncertainty and risk. The theoretical frameworks of Pratt (1964), Turnovsky et al. (1980) and Schmitz et al. (1980) reveal why price stability is preferred. Turnovsky et al. showed how a consumer’s preference for price stability depended on only a handful of parameters, and the authors then derived a similar measure for multiple commodities. Additionally, the empirical framework developed by Finkelshtain and Chalfant (1991, 1997) confirms predictions of the preference for price stability. On the supply side, under certain circumstances—even under high levels of competition—sellers and producers may benefit from price volatility (Oi, 1961).

With respect to the issue of welfare and price volatility, in development economics questions are centered on how commodity price volatility affects the welfare of households in contexts where production and consumption smoothing is often difficult. Output price uncertainty generally causes firms to employ fewer inputs, forgoing expected profits in order to hedge against price volatility (Baron, 1970; Sandmo, 1971; Barrett, 1996 for farms). When the analysis of commodity price risk is extended to individual consumers (Deschamps, 1973; Hanoch, 1977; Turnovsky et al., 1980; Newbery and Stiglitz, 1981), these are generally thought to be price risk-loving for a specific commodity when the budget share of that commodity is not too large.

In sum, there is no specific link between price volatility and market efficiency as defined and — used in this study. However, given that volatility might either increase transaction costs since risk has to be mitigated or lead to missing marketsless volatility will lead to more efficient market transactions than more volatility. For this reason, in this study, above average levels of price volatility are an anomaly that requires study and explanation.

4
# Pass-through

Price pass-through is the most common measure of how transmission between markets happens. Following Fackler and Goodwin (2001), pass-through happens when cost or price shocks arising in one location are transmitted to the other. Specifically, the market for good � in region � is said to be spatially integrated with that of region � if a shock that shifts, for example, demand in � but not in � affects the price in both � and �. Even if large price differences exist between a pair of locations, if shocks are transmitted, then markets are considered to be integrated and efficient.

The magnitude as well as the speed of the pass-through indicates how well markets transmit information about changes in costs or prices. For this reason, pass-through is directly related to the efficiency and integration of markets. In addition, the nature of pass-through may also indicate characteristics about the market structure (competitive or otherwise).

The empirical literature finds that pass-through is often incomplete (Campa and Goldberg, 2005; Goldberg and Hellerstein, 2008). For example, a one dollar rise in the per unit cost of an input is not always transmitted as a dollar increase in retail prices for that unit. Even when accounting for lags several studies confirm this (Campa and Goldberg, 2006; Nakamura, 2008; Nakamura and Steinsson, 2008; Hellerstein, 2008; Goldberg and Campa, 2010; Nakamura and Zerom, 2010; Eichenbaum et al. 2011). Incomplete price pass-through is attributed to remoteness of markets, trade barriers, or government interventions.

The magnitude of pass-through can also vary with market structures (for example, see Jackson, 1997). The level of competition in a market matters for the intensity of transmission of cost changes into final prices. Pass-through is complete (100 percent) in environments with perfect competition.<sup>5</sup> For all other market structures, the expected pass-through is a bit ambiguous and depends on other conditions. With sufficiently high transport costs, the passthrough could even be zero with perfect substitutes.<sup>6</sup> Under monopolistic competition, the pass-through decreases with the transportation costs (Engel and Rogers, 1996). Incomplete pass-through can therefore be the result of anti-competitive behavior (Domberger, 1979).

In addition to its magnitude, pass-through from costs to prices may have varying delays or ‘speed of adjustment’ across markets (Dixon, 1983). The existence of pass-through delays is explained by the fact that business may incur costs (menu costs) to change prices (Rotemberg, 1983; Nakamura and Zerom, 2010; Klenow and Kryvtsov, 2008). Eichenbaum et al. (2011) argue that retail prices generally do not change in the absence of a change in costs but conversely changes in costs may not be sufficient to trigger a change in retail prices. Nakamura and Steinsson (2008) and Kehoe and Midrigan (2007) find that when sales (discounts) are excluded, prices are rather inertial: prices change on average every 11 months

> 5 In an environment with constant marginal costs and linear demand, pass-through for a monopolist is predicted ����� �� ������ to be 50 percent. In general, pass-through for the monopolist is defined by ��� ~~,~~ while pass����� �� �������� ������� � through for a competitive markets is defined by: ���<sup>���������� �� �������� ������������</sup> .

> ��<sup>���������� �� ������</sup> . ���������� �� ������

> 6 ���� ���� ��� ��1 ����� where ��0 is the transportation cost. This equation illustrates the arbitrage between two points A and B when the good sold in A is a perfect substitute to the good sold in B. If the price in A is within the band expressed in the inequality, there is no exchange. On the edges of the band, pass-through is complete.

5
for the Nakamura and Steinsson study and every 4.5 months for the study carried out by Kehoe and Midrigan.

Prices in some markets may be slow to change compared to costs because the physical good may only be a relatively small part of the unit costs. When this is the case, the buyer also pays for additional services (marketing or/and advertisement) and local costs (wage, labor, local taxes, local transportation services, retail services). These additional costs may be substantial compared to the unit cost of the physical good (Burstein et al. 2003). This implies that even a significant increase in the unit cost of an imported factor of production or in wholesale prices may increase retail prices by only a small fraction of total costs (Burstein et al., 2003; Burstein et al., 2007; Goldberg and Campa, 2010; and Nakamura and Zerom, 2010). For example, Goldberg and Hellerstein (2008) indicate that response of prices to exchange rates in the beer industry is small mainly because of local costs that are responsible for approximately half of the observed inertia of retail prices. So even though changes in exchange rates should affect the price of beer bought and sold internationally, changes in retail prices do not reflect changes in exchange rates.

# Behavior of consumer prices in Mexico

A few studies for Mexico analyze prices from a microdata perspective. One particular finding in some of these studies is the asymmetry between the frequency of upward and downward price changes, with upward movements being more common, suggesting some inefficiencies in price adjustments (Gagnon, 2009 and Ysusi, 2010). Vaughan (2013) finds some evidence of market integration in the form spatial correlation of cities’ price indexes for the same good, but this only holds in the presence of structural breaks (i.e., a change of indexes from nonstationary to stationary processes); once a structural change takes place, cities’ prices seem to be driven by internal (idiosyncratic) factors rather than spatially or regionally. Finally, Gagnon (2006) identifies that in periods of low inflation (below 10-15%), such as during our sample period,<sup>7</sup> the adjustment in inflation is mostly driven by the average magnitude of price changes rather than by the frequency of changes. The frequency of changes plays almost no role in such adjustment.

# Effects of the entry of a large retailer on prices

There is documented evidence on the effect the entry of a large retailer has on retail prices. Basker (2005) and Fishman (2006) indicate that Wal-Mart charges lower prices in the markets it enters, inducing other retailers to reduce their prices too. Thus, a possible consequence of higher competition is a lower price dispersion. Fishman (2006) also hints at the possibility of a reduction in price volatility when Wal-Mart enters a market, because it smooths fluctuations in the seasonality of some goods’ prices. Relatedly, Atkin et al. (2015) find that the arrival of global retail chains has led to welfare gains in average Mexican households, mainly driven by reductions in the costs of living.

# DATA

To identify and describe how prices for certain well-specified commodities function across time and space for markets across Mexico, we look at price dispersion, price pass-through and price volatility temporally and geographically. To explain how these dimensions were

> 7 The highest annual CPI inflation level in our sample is 4.97%.

6
formulated and estimated, we first provide the reader with a description of the data use and then the empirical strategy.

# The INEGI INPC microdata

The data are a time series of urban retail prices collected by the Mexican Institute of Statistics, INEGI (Spanish acronym), originally collected bi-weekly to estimate consumer price indexes. Geographic data are mapped to the price data to have information on the location where the data were collected and to exploit heterogeneity in location characteristics in the analysis. There is also information on the type of outlets from which these retail prices were collected and this information is used in the analysis as well.

In addition to understanding the patterns of how markets work, this novel retail price data set is also used to identify and understand how entry of large retailer stores affected the performance of the retail markets these new stores serve compared to those they do not. In addition, using the same micro-level price data, this research identifies and explains the effect of competition policy changes.

The database used to study the functioning of markets consists of time series of retail prices collected by INEGI used for the computation of Mexico’s consumer price index (INPC). The INPC is published every two weeks and takes price quotes from 46 cities. The prices of cement are supplemented with INEGI’s database on residential construction prices, which has the same characteristics as the INPC data, but with fewer observations within cities. The period covered in this study goes from January 2010 to December 2015.

Table 1. Cities and Regions in the INEGI INPC database

|**Region**|**City**|**Abbrev.**|**State**|**Region**|**City**|**Abbrev.**|**State**|
|---|---|---|---|---|---|---|---|
||Mexicali<br>~~Tijuana~~|MXL<br>~~TIJ~~|Baja California||Acapulco<br>~~Iguala~~|ACA<br>~~IGU~~|Guerrero|
|Northern|~~La Paz~~|~~LAP~~|~~Baja California Sur~~||~~Tulancingo~~|~~TUL~~|~~Hidalgo~~|
|border|~~Acuña~~|~~ACU~~|~~Coahuila~~||~~Toluca~~|~~TOL~~|~~State of Mexico~~|
||~~Juarez~~|~~JUA~~|~~Chihuahua~~|Center‐|~~Cuernavaca~~|~~CUE~~|~~Morelos~~|
||Matamoros|MAT|Tamaulipas|south|Puebla|PUE|Puebla|
||Tepic|TPC|Nayarit||~~Tlaxcala~~|~~TLAX~~|~~Tlaxcala~~|
|Nh|Culiacan|CUL|Sinaloa||~~Veracruz~~|~~VER~~||
|ortwes~~t~~|~~Hermosillo~~|~~HMO~~|||Cordoba|COR|Veracruz|
||Huatabampo|HUA|Sonora||San Andres Tuxtla|SAT||
||Torreon|TOR|Chil||~~Campeche~~|~~CAMP~~|~~Campeche~~|
||~~Monclova~~|~~MVA~~|oaua||~~Tapachula~~|~~TAP~~|~~Chiapas~~|
||Chihuahua|CHIH|Chihh||~~Oaxaca~~|~~O~~AX|O|
||Jimenez|JIM|uaua|South|Tehuantepec|TEU|axaca|
|Norteast|~~Durango~~|~~DGO~~|~~Durango~~||~~Chetumal~~|~~CHE~~|~~Quintana Roo~~|
||~~Monterrey~~|~~MTY~~|~~Nuevo Leon~~||~~Villahermosa~~|~~VSA~~|~~Tabasco~~|
||~~Tampico~~|~~TAM~~|~~Tamaulipas~~||~~Merida~~|~~MID~~|~~Yucatan~~|
||~~Fresnillo~~|~~FRE~~|~~Zacatecas~~|Mexico|Mexico City||Federal District and|
||~~Aguascalientes~~|~~AGS~~|~~Aguascalientes~~|City|Metro Area|MX|State of Mexico|
||~~Colima~~|~~COL~~|~~Colima~~|||||
||Leon<br>~~Cortazar~~|LEON<br>~~CTZ~~|Guanajuato|||||
|Center‐<br>north|Guadalajara<br>Tepatitlan|GDL<br>TEP|Jalisco|||||
||~~Morelia~~<br>Jacona|~~MOR~~<br>JAC|Michoacan|||||
||~~Queretaro~~|~~QRO~~|~~Queretaro~~|||||
||San Luis Potosi|SLP|San Luis Potosi|||||

All Mexican states and the Federal District (which roughly corresponds to the Mexico City Metro Area) are represented in the database with at least one city. INEGI groups these cities 7
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whole – Alpura brand – 1lt carton”, “beef: ground –unbranded – unpackaged – by the bulk”, among many others.

INEGI follows a wide range of specifics within a certain generic category. The aim of casting a wide net is to gather as much information from markets as possible and to avoid capturing price behaviors that may be idiosyncratic to certain brands or varieties. In some cases, this wide net approach is also due to the fact that consumption habits and tastes vary regionally and the aim is to capture all habits across Mexico. A clear example of this is bean consumption: people from southern and central states tend to prefer (and consume more) black beans, whereas people from the north and the west usually consume pinto beans (and almost no black beans at all). Accordingly, INEGI’s price gatherings of the generic category “beans” in the south and the center of the country contain more information of the specific good “black beans” and much fewer price quotes of the specific “pinto beans”. The opposite is the case for cities in northern and western states.

In sum, INEGI’s database contains detailed information of the characteristics of wide range of goods. We were able to track specifics precisely and to distinguish them from other goods that may be similar. As a result, it was possible to analyze goods that are exactly the same across cities and time; we compared apples with apples. Also, INEGI’s wide coverage of generics means that price data for these may be heterogeneous within some generic categories. In principle, higher levels of heterogeneity should not pose a problem for our analysis. As long as a specific is widely covered across and within cities and is consistently followed through time, heterogeneity in the price data is, if anything, a potential advantage to exploit in the empirical strategy.

# Challenges when using the INPC data

While INEGI does follow all generics in all cities, there were cases where specifics surveyed in certain cities or regions did not match (strictly speaking) with the ones followed in other geographical areas. This seemed to be apparent independently of consumption habits and tastes or availability of certain specifics within a city. This sometimes happened because INEGI’s database is intended to be representative only at the national level, a requirement that allows degrees of freedom on goods selection across cities.

An illustrative example for this is soda. Soda is widely available basically everywhere and it comes in different presentations, sizes, flavors and brands. There is no doubt that many brands and sizes (for example, Coca Cola – 600 ml bottle) are sold in all cities and in practically all types of outlets. Thus, it would be expected to count with several price quotes in all cities of such common specifics. However, what we see is that INEGI collected price data on certain varieties and brands in some cities and other varieties and brands in other cities. The price of specific “Coca Cola – 600ml” is widely tracked in a set of cities, while in others the specific “Pepsi – 600ml” is tracked. We know that both specifics are widely available and sold in all cities, but the data collection does not reflect this.

This fact limited the number of exact matches of specific goods that could be compared across cities and represented a challenge to the empirical strategy. For some goods, we were able to obviate brand and analyze specifics of exactly same characteristics (variety, size, package, etc.) as if they were the same good. Unfortunately, we also had to drop entire generic categories simply because the set of generics was too heterogeneous and prices across these 9
difficult to compare. Among some of the dropped generics are detergents, dishwashing liquid, body soap and toilet paper.

Table 2. Description of goods included in the analysis

|**Group**|**Good**|**Variety**|**Size**|**Brand**|**Unit of**<br>**measure**|
|---|---|---|---|---|---|
|Grains|Beans<br>Rice|Pinto and black<br>Super extra|1 kg<br>1 kg|Most common brands<br>Most common brands|per kg<br>per kg|
|Tortilla&|Bolillo bread|‐|per piece|Unbranded|per piece|
|<br>bd|Concha bread|‐|per piece|Unbranded|per piece|
|rea|Corn tortilla|‐|by the bulk|Unbranded|per kg|
||Eggs|Brown and white|per piece|Most common brands|per piece|
||Eggs|Brown and white|12 pack|Most common brands|per piece|
|Eggs & milk|Eggs|Brown and white|18 pack|Most common brands|per piece|
||Eggs|Brown and white|30 pack|Most common brands|per piece|
||Milk|Whole|1 lt|Most common brands|per lt|
||Water|‐|1 lt|Most common brands|per lt|
|Beverages|Water|‐|1.5 lt|Most common brands|per lt|
||Soda|‐|2 lt|Most common brands|per lt|
||Soda|‐|600 ml|Most common brands|per lt|
||Beef|Chop|by the bulk|Unbranded|per kg|
||Beef|Ground|by the bulk|Unbranded|per kg|
||Bee|Rib|by the bulk|Unbranded|per kg|
||Beef|Steak|by the bulk|Unbranded|per kg|
|Meat|Chicken|Roasted|by the bulk|Unbranded|per kg|
||Chicken|Whole|by the bulk|Unbranded|per kg|
||Chicken|Breast|by the bulk|Unbranded|per kg|
||Pork|Rib|by the bulk|Unbranded|per kg|
||Pork|Steak|by the bulk|Unbranded|per kg|
||Apple|Golden|by the bulk|Unbranded|per kg|
||Banana|Cavendish|by the bulk|Unbranded|per kg|
||Guava|‐|by the bulk|Unbranded|per kg|
||Lime|Key (Mexican)|by the bulk|Unbranded|per kg|
||Muskmelon|‐|by the bulk|Unbranded|per kg|
|Fruits|Orange|Valencia|by the bulk|Unbranded|per kg|
||Papaya|Maradol|by the bulk|Unbranded|per kg|
||Pear|D'Anjou|by the bulk|Unbranded|per kg|
||Pineapple|‐|by the bulk|Unbranded|per kg|
||Plantain|‐|by the bulk|Unbranded|per kg|
||Watermelon|‐|by the bulk|Unbranded|per kg|
||Avocado|Hass|by the bulk|Unbranded|per kg|
||Cabbage|‐|by the bulk|Unbranded|per kg|
||Zucchini|‐|by the bulk|Unbranded|per kg|
||Carrot|‐|by the bulk|Unbranded|per kg|
||Chayote|‐|by the bulk|Unbranded|per kg|
||Jalapeño pepper|‐|by the bulk|Unbranded|per kg|
||Poblano pepper|‐|by the bulk|Unbranded|per kg|
|Vegetables|Serrano pepper|‐|by the bulk|Unbranded|per kg|
||Cucumber|‐|by the bulk|Unbranded|per kg|
||Lettuce|Romaine|by the bulk|Unbranded|per piece|
||Onion|Common|by the bulk|Unbranded|per kg|
||Potato|White|by the bulk|Unbranded|por kg|
||Tomatillo|‐|by the bulk|Unbranded|por kg|
||Tomato|Beefsteak|by the bulk|Unbranded|por kg|
||Tomato|Roma|by the bulk|Unbranded|por kg|
||Salt|Table salt|1 kg|Most common brands|por kg|
||Sugar|Refined|1 kg|Most common brands|por kg|
|Other|Sugar|Refined|2 kg|Most common brands|por kg|
||Cooking oil|Mixed|1 lt|Most common brands|per lt|
||Cement|Portland|50 kg|Most common brands|per 50 kg|

# Sample selection strategy

We focused on analyzing consumable commodities—perishables and non-perishables. Moreover, we chose commodities that are bought and sold in relatively thick markets on both the demand and supply sides, have relatively low information costs to determine differences 10
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
considered non-tradeables. We relied on the database sources used to construct the monthly commodity prices of the World Bank’s Pink Sheet and the International Monetary Fund (IMF) Commodity Prices databases. Given that our database contains bimonthly prices, the sources mentioned above were used only as reference in finding more frequent price collection. For goods that did not appear on any of the World Bank and IMF databases, we collected international prices from the US Department of Agriculture (USDA), Market News. We used shipping point prices for the most common varieties and presentation in which goods are sold. These shipping point prices represent first on board (FOB) prices of open market (spot) sales by first handlers at point of production or port of entry on products of generally good quality and condition. The USDA data may not always represent a world price but the specificity and high frequency of the price data collection makes it a valuable source. Also, this database contains at least an international price of a country that happens to be Mexico’s most important trade partner. Table 3 contains a description of the data gathered.

Table 3. International prices database description

|**Good**|**Intl' price**<br>**available?**|**Description**|**Country** **of** **origin**|**Unit** **of** **measure**|**Source**|
|---|---|---|---|---|---|
|Beans<br>Rice|<br>|US average bid price|US|100 lb bag|US Department of Agriculture|
|Bolillo bread||||||
|Concha bread||||||
|Corn tortilla*|<br>|US (Gulf), Maize (US No. 2, Yellow)|US|per tonne|FAO|
|Eggs<br>Milk||Shell Eggs: Weekly Combined Regional||||
|Water<br>Soda||||||
|Beef||CIF US import price|Australia|per lb|Meat and Livestock Australia|
|Chicken||FOB broiler/fryer prices|US|per lb|US Department of Agriculture|
|Pork||Lean Hogs Futures (HEZ6)|US|Per tonne|investing.com|
|Apple||Shipping point average price|US|36 & 40 lb carton|US Department of Agriculture|
|Banana||US East Coast ‐ Main Brands, f.o.r.|Central America|per tonne|FAO, The World Bank|
|Guava||||||
|Lime||Shipping point average price|Mexico|40 lb carton|US Department of Agriculture|
|Muskmelon||Shipping point average price|Brazil, Central America, Mexico, US|30 & 40 lb carton|US Department of Agriculture|
|Orange||Shipping point average price|US|38 lb carton|US Department of Agriculture|
|Papaya||Shipping point average price|Brazil, Central America, Mexico|25, 40 lb carton; 3.5 kg container|US Department of Agriculture|
|Pear||Shipping point average price|Argentina, Chile, US|45 lb carton; 18 kg container|US Department of Agriculture|
|Pineapple||Shipping point average price|Central America, Mexico|20 lb carton|US Department of Agriculture|
|Plantain||US East Coast ‐ Main Brands, f.o.r.|Central America|per tonne|FAO, The World Bank|
|Watermelon||Shipping point average price|Central America, Mexico, US|Several packages, price per lb|US Department of Agriculture|
|Avocado||Shipping point average price|Mexico, Chile, Peru|23 lb carton/flat|US Department of Agriculture|
|Cabbage||Shipping point average price|US|50 lb carton|US Department of Agriculture|
|Carrot||Shipping point average price|Mexico, US|25 & 50 lb sack|US Department of Agriculture|
|Chayote||Shipping point average price|Central America, Mexico|20 & 40 lb carton|US Department of Agriculture|
|Cucumber||Shipping point average price|Central America, Mexico, US|55 lb carton|US Department of Agriculture|
|Jalapeño pepper||Shipping point average price|Mexico|28 lb carton|US Department of Agriculture|
|Lettuce||Shipping point average price|US|40 & 50 lb carton|US Department of Agriculture|
|Onion||Shipping point average price|US|25 & 50 lb sack|US Department of Agriculture|
|Poblano pepper||Shipping point average price|Mexico|28 lb carton|US Department of Agriculture|
|Potato||Shipping point average price|US|50 lb carton/sack; 2000lb sack|US Department of Agriculture|
|Serrano pepper||Shipping point average price|Mexico|28 lb carton|US Department of Agriculture|
|Tomatillo||Shipping point average price|Mexico|40 lb carton/container|US Department of Agriculture|
|Tomato||Shipping point average price|Mexico, US|20 & 25 lb carton/flat|US Department of Agriculture|
|Zucchini||Shipping point average price|Mexico, US|21 & 28 lb carton|US Department of Agriculture|
|Salt||||||
|Sugar||US Sugar # 11 futures (SBH7)|US|per lb|investing.com|
|Cooking oil||Soybean oil futures (ZLZ6)|US|per lb|investing.com|
|Cement||||||

# Market structure and competition data

We tracked sanctions imposed by COFECE, Mexico’s competition agency to study prices in markets with possible competition issues. The voluminous set of documents on investigations, resolutions and opinions on competition matters was used to identify markets 12
with potential competition-related problems. COFECE’s research information covers analyses for different types of goods (or categories of goods), for several types of economic sectors (including retailing), in different regional levels. We found that during the period of analysis, COFECE fined industries in poultry, soda, tortilla, avocado and cement. The businesses fined by COFECE were large companies with presence at the national level, which allowed us to analyze the effect of the sanctions in all city markets.

We also use data on the entry of a large retailer store in Mexican cities through time. This large retailer operates several types of retail stores aimed to sell to different types of customers. There are four store brands relevant to this study and we distinguished each for the analysis: 1) the first brand is basic and austere mini- and super-markets that mostly sell groceries and personal care products at the lowest price possible; 2) the second brand sells a wide range of goods, from groceries to electronics and small appliances; 3) the third brand is premium supermarkets focused on higher-end groceries; and 4) the fourth brand stores are a warehouse club.

We are able to follow the openings of these four kinds of stores in all cities in our database. The large retailer provides information on store openings in their monthly sales reports, which are available in their webpage. Thus, we can estimate the effect of the entry of each of the store brands, either as the group as a whole or by type of store. The first brand stores are by far the most common of all this large retailer’s stores, and expanded aggressively during the time period (722 total openings in the sample, including both super- and mini- markets). Then, the second and fourth brand stores opened less frequently (63 and 40 openings, respectively), while third brand store openings were the least common (23 openings).

# EMPIRICAL STRATEGY

The empirical strategy is divided into two activities. First, we estimate indicators to identify and understand how markets are working. This way we can distinguish those markets that seem to be working relatively well from those that work less efficiently. The second step consists in analyzing the effect that the described trade and market structure variables play in the functioning of such markets.

It is important to understand what we mean by market efficiency through the use of the indicators discussed above, in the literature review. Defining efficient markets is the first task of the empirical strategy.

# Efficient market and its characteristics

To identify and understand which markets are functioning well, we first define the performance criteria. Our criteria equate a well-functioning market with an efficient market. More precisely, since all of the indicators of efficiency used are relative, we define a market that is functioning relatively well as a market that is working relatively more efficiently than other markets.

13
Market efficiency refers to the situation in which prices reflect, fully and immediately, all information available, and where no opportunities of arbitrage exist.<sup>9</sup> This definition sets a high standard. It is unlikely that many markets function with perfect efficiency. Many markets do not adjust prices at all times for all locations, for every buyer and seller in ways that fully and immediately reflect all relevant information that materializes. For a variety of reasons, inefficiency in markets is a fact of life. As a general rule, however, markets tend to adjust prices in response to new information. Some markets are better at doing this faster and more completely than others. The point is to understand why some markets can do this relatively well, while others seemingly do not. Since there is not a perfectly efficient market, this research examines gradations of efficiency by comparisons.

The analysis focuses on questions such as: why arbitrage may be relatively more apparent in, say, Market 1 than in Market 2, why there may be relatively more complete and immediate cost pass-through in one market compared to another, why prices for good 1 are more volatile than for good 2, etc. This research is comparative in nature in the sense that the performance of markets is stacked against each other. For that reason, it is important to set benchmarks to which the proposed measures of market efficiency are compared.

The canonical, hyper-efficient market is used as a benchmark in this study, despite the fact that perfectly efficient and fully competitive markets are, at best, rare. For the same reason that physicists use frictionless models as the starting point to describe important features of the physical world, economists use the functioning of a perfectly competitive and efficient market to provide insights into important features of how markets have the potential to work. When the functioning of the ideal and observed markets does not match, this mismatch affords the opportunity to explore why this is the case. Also, the variation in performance of markets among themselves—that is, heterogeneity in market efficiency—affords an opportunity for further research as well. Thus, comparisons between the ideal benchmarks and the data are used throughout this study. It is important to begin here by explaining the efficient market benchmark.

The basic feature of an efficient market is that prices reflect all information available. If a market is efficient, price signals will be available to all market agents, in the blink of an eye and at zero cost. With every market participant having the same information, prices should behave in the same way. Stiff price competition is the engine that incentivizes all market agents to remain informed and to use all available information.

The ability of buyers to switch, instantaneously, from higher priced sellers to lower priced ones, is based on two other features that characterize competitive markets: zero transaction costs and zero information costs. Zero transaction costs means that a buyer will assume no additional cost in switching from one seller to another. With no transportation costs, for example, there is no additional cost to buying from one seller as opposed to another. In addition to zero transaction costs, perfect information translates into instantaneous knowledge about all prices, and all dimensions that are required to complete the buying transaction with any seller. All sellers have to respond immediately to changes in prices or lose all sales or gain all sales but at prices that represent a loss for each unit sold. These

> 9 Concerns about the efficiency of markets are most often relegated to discussion about financial markets. Indeed, the concept of market efficiency as described here was first introduced by Fama (1970) in the context of foreign exchange markets, but it can be easily extended to any market.

14
assumptions about instantaneous price changes and symmetry between upward and downward price movements will also be used to indicate if a market is working relatively efficiently and exhibits signs of the use of market power.

In sum, the prices of efficient markets behave like one large, agglomerate market—very much like a school of sardines swimming in the ocean. Even with external shocks, prices in efficient markets would quickly converge back to equilibrium. The question for this study is to ascertain just how closely this characterization resembles the behavior of prices in actual markets.

# Definition of markets

The definition of markets is the foundation to the rest of the empirical strategy; the market is the unit of analysis for all regressions, not descriptive statistics, however. Markets are defined as the combination of location, commodity and outlet type. This definition is far from perfect. A better definition would be one used by antitrust authorities. In antitrust economics, <mark>the relevant market is defined by the cross elasticity of demand or cross-price elasticity of demand. Elasticities measure the responsiveness of the demand for a good to a change in the price of another good.</mark><sup>10</sup> When consumers substitute one good in response to small but significant and non-transitory price increases with another product, antitrust economists conclude that these products compete against each other and are therefore in the same market.

By using a location-commodity-outlet type triplet we likely define markets more broadly than the antitrust definition. This is most likely to affect the price dispersion indicator where dispersion may be the result of aggregating markets that do not belong together, and therefore have different prices. At the same time, the definition includes economically relevant factors that shape how products compete and prices are derived and respond. This makes our definition of markets congruent with the definition of ‘relevant markets’ from antitrust economics.

# Step 1: Estimation of Indicators

In order to assess how markets are working, we estimate indicators to study markets in the following three dimensions:

- Price dispersion;

- Price volatility; and

- Integration with international markets;

- Pass-through speed

- Pass-through magnitude

- Pass-through symmetry

As described above, each of the indicators plays an important role in understanding the functioning of markets.

> 10 It is measured as the percentage change in demand for the first good that occurs in response to a percentage change in price of the second good.

15
| <u>N _</u><sup>Deviation</sup> <u>\N</u> i=1(Pit <u>—</u> Pr)? CV, =<sup>Standard</sup> an Mean 7 P,

Pit Pr Returns ~~In(P, /Py~~ = ~~(Tee)~~ k Volatility = Standard Deviation (Returns) k=1
WP, t Zt Zt P, =a) + a,WP, +z; APit-1 AWPy ¢-4 Zt-1 APt ¢-1 t-— 1 t AW Py ¢-1 APit-1 = Yo + V1 AWPrt-1 — PoZt-1 + €t where Zp-1 = ECT; ¢~1 Y1 Po ECT 1-1 APet-1 = Bo + BiAWPee-1 — PrECT; + O2ECT;_1 + & Zt-1
is shown in Equation (6). Positive components (errors) ������� imply that domestic prices are temporarily above equilibrium, and that the processed adjustment implies a price decrease. Negative components (errors) ������� imply the converse.

This strategy was followed for all goods. We focus on series that appear to be cointegrated with the international prices or show to be stationary, otherwise any relation between local and international prices could be spurious. In order to evaluate this, we perform the Augmented Dickey-Fuller GLS test, which is better suited for short samples (in our case, at most series can be 144 observations long). In the descriptive statistics, we present passthrough indicators at city level, while in the regressions with the control variables we use the city-outlet level indicators.

# DESCRIPTIVE STATISTICS

We describe and analyze how markets function in two ways. First, we use heat maps that characterize how price indicators behave for each good and city across the time series. Heat maps provide a visual idea of which goods and in which cities prices have a tendency toward higher efficiency. In the following section, the results of fixed effects regressions provide information on which characteristics play an important role in the way markets work.

However, it is important first to understand the macroeconomic environment in which Mexico experienced during the period of study. Figure 2 indicates the evolution of prices, GDP, exchange rates and unemployment rates; low and falling CPI and exchange rates, a modestly falling GDP rate of growth and a very modestly falling unemployment rate.

Figure 2. Macroeconomic indicators of Mexico during the period of study <!-- Start of picture text --> a) Inflation and Exchange rate b) GDP growth and Unemployment<br>6.0 18.0 7.0<br>GDP - annual growth rate<br>Unemployment rate - %<br>17.0<br>6.0<br>5.0<br>16.0<br>5.0<br>4.0<br>15.0<br>4.0<br>3.0 14.0<br>3.0<br>13.0<br>2.0<br>2.0<br>12.0<br>1.0 CPI - annual growth rate 11.0 1.0<br>Exchange rate - MXN/USD (right)<br>0.0 10.0 0.0<br>Jan-2010 Jul-2010 Jan-2011 Jul-2011 Jan-2012 Jul-2012 Jan-2013 Jul-2013 Jan-2014 Jul-2014 Jan-2015 Jul-2015 Q1 2010 Q3 2010 Q1 2011 Q3 2011 Q1 2012 Q3 2012 Q1 2013 Q3 2013 Q1 2014 Q3 2014 Q1 2015 Q3 2015<br><!-- End of picture text --> Source: INEGI, Bank of Mexico.

Source: INEGI.

18
Tables 4 to 9 provide visual information on the performance of each price indicator in the form of heat maps. In all cases except for the case of price levels, heat maps compare values of indicators across all goods and cities. A cell in green means that the value is in the lowest 10<sup>th</sup> percentile across the whole sample of indicators. A cell in red means that the value is in the 90<sup>th</sup> percentile while yellow is a value statistical median. In the case of price levels, colors compare prices by row, that is, by good, since it does not make sense to compare price levels across goods and cities but within goods across cities.

Table 4 shows average price levels across cities for each commodity. Prices in the North tend to be higher, especially along the US-Mexico border and northwest regions. Cities in central and southern parts of the country tend to have lower prices. Noticeably, prices of certain goods are more or less consistently lower in the South vis-a-vis central states and vice versa. The South has, roughly speaking, lower prices for some, non-perishable (salt, sugar, cooking oil) goods as well as some meat products, but higher prices for vegetables and some fruits.

Price dispersion patterns are clear by good, but a less distinct pattern across cities (Table 5). In general, dispersion seems consistent across goods more than location (or store type). Most fruits and vegetables indicate higher dispersion than non-perishables. Also prices for beans and bread indicate relatively higher price dispersion. On average, the standard deviation of prices is on average 0.15 the size of the average price within a city.

Price volatility is largely influenced by the type of good. Regional factors, however, play a significant role (see Table 6) as well. Prices of fruits and vegetables are by far the most volatile, showing an average volatility of 16 percentage points (pp), while the average volatility of the rest of goods is four time less, around 4 pp. Recall that volatility is defined as the standard deviation within a 6-month period (12 observations), thus volatility of 16 pp implies that inflation rates of prices tend to move around 16 pp around its average inflation within such period. Geographical patterns are less obvious, but present. Roughly speaking, lower volatility is apparent in cities located in central states, including Mexico City.

The extent to which shocks in international prices transmit to local prices is shown in Table 7. Pass-through measures shown in this table include coefficients of long-term relationship regressions whose significance is below 0.20 and whose series are either cointegrated or stationary. Values of zero in Table 7 refer either to correlated or stationary series whose longterm regression coefficients were equal to zero or statistically insignificant (p-value 0.20 or higher in this case). The magnitude of the pass-through in prices is particularly high for meat products, especially in the varieties of beef and chicken. In many cases, local prices overshoot when adjusting to shocks in international markets (shown in pass-through values above 100, implying that local prices absorb more than 100% the adjustment in international prices). Also, the magnitude of price pass-through is comparatively high for bananas and avocados. In the case of avocado, such pass-through magnitudes correspond with the fact that Mexico is a major exporter of this good. The rest of goods, on average, indicate a magnitude of price pass-through of around 36, which is a relatively low value. This implies that local prices in general tend to absorb 36% of the changes in international prices in the long-term. This is an indication that some Mexican markets, especially those for fruits and vegetables are relatively immune to the influence of changes in prices of international markets. This is not uncommon; perishable goods are more likely to be sold in local markets as compared to cement, soda or bottled water.

19
The speed of adjustment is the companion price transmission measure to the magnitude of pass-through. Table 8 contains results that indicate that the speed of adjustment in prices is perhaps more uniform across goods. In similar fashion to the magnitude of pass-through, Table 8 shows coefficients of Error Correction Model (ECM) regressions with significance below 0.20. Also, zero values are due to zero-valued coefficients or statistically not significant coefficients. On average, prices adjust at a rate of 22% each time period, implying that it takes approximately two and a half months (5 two-week periods) for local prices to fully incorporate shocks from international markets. Local prices of chicken are relatively more sensitive to changes in international prices in terms of both magnitude and speed to shocks. In comparison, many coefficients for meat products are not significant, suggesting that speeds of adjustment are much slower. Prices for many fruits and vegetables adjust relatively quickly, implying that, while they might not absorb shocks fully in terms of magnitude, these are absorbed faster than other goods, in some cases within a month.

Price transmission asymmetries between positive and negative shocks are less frequent (see Table 9). In general, positive and negative shocks in international prices tend to appear at the same frequency in local markets. In some cases, prices for goods appear to have somewhat consistent positive asymmetries (i.e. local prices adjusting faster to positive shocks than to negative ones), such as papaya, carrot and chayote, and others with negative asymmetries like the case of watermelon and some meat products. As pointed out before, this asymmetry in price adjustments could indicate market power. However, to conclude that it is market power as the explanation for this finding would be premature.

20
<u>Table 4.</u> ~~<u>Av</u>~~ <u>erage prices in cities</u>

||ae .~~v~~erage prces n ctes<br>South<br><br>Northern border<br>Northwest<br>Northeast<br>Center north<br>Center south|
|---|---|
||MXL<br>TIJ<br>LAP<br>ACU<br>JUA<br>MAT<br>TPC<br>CUL<br>HMO<br>HUA<br>TOR<br>MVA<br>CHIH<br>JIM<br>DGO<br>MTY<br>TAM<br>FRE<br>AGS<br>COL<br>LEON<br>CTZ<br>GDL<br>TEP<br>MOR<br>JAC<br>QRO<br>SLP<br>ACA<br>IGU<br>TUL<br>TOL<br>CUE<br>PUE<br>TLAX<br>VER<br>COR<br>SAT<br>CAM<br>TAP<br>OAX<br>TEU<br>CHE<br>VSA<br>MID<br>MX|
|Beans|24<br>24<br>23<br>21<br>18<br>23<br>~~2~~4<br>25<br>18<br>24<br>~~2~~0<br>20<br>19<br>18<br>20<br>22<br>19<br>21<br>~~2~~1<br>21<br>24<br>23<br>26<br>23<br>21<br>22<br>20<br>1~~8~~<br>24<br>22<br>24<br>20<br>23<br>23<br>21<br>22<br>19<br>21<br>~~1~~9<br>21<br>20<br>18<br>20<br>20<br>1~~8~~<br>24|
|Rice|18<br>16<br>15<br>12<br>13<br>12<br>~~1~~4<br>19<br>12<br>12<br>~~1~~6<br>16<br>13<br>14<br>16<br>13<br>14<br>11<br>~~1~~3<br>14<br>16<br>13<br>15<br>15<br>12<br>12<br>15<br>1~~4~~<br>13<br>13<br>15<br>17<br>15<br>15<br>16<br>12<br>12<br>14<br>~~1~~6<br>12<br>12<br>13<br>17<br>15<br>1~~7~~<br>16|
|Eggs ‐ per piece<br>|2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>1<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>1<br>1<br>~~2~~<br>2<br>1<br>2<br>2<br>2<br>1<br>2<br>2<br>2<br>2<br>2<br>2<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>|
|Eggs ‐ 12 pack|2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>~~2~~<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>~~2~~<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2|
|Eggs ‐ 18 pack|2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>~~2~~<br>2<br>2<br>2<br>~~1~~<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2|
|Eggs ‐ 30 pack<br>|2<br>2<br>2<br>1<br>1<br>2<br>2<br>1<br>1<br>2<br>2<br>2<br>2<br>1<br>2<br>2<br>~~2~~<br>2<br>2<br>2<br>2<br>~~2~~<br>1<br>2<br>2<br>2<br>1<br>1<br>2<br>1<br>1<br>1<br>1<br>1<br>2<br>2<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>|
|Milk|15<br>14<br>15<br>13<br>13<br>12<br>~~1~~3<br>14<br>14<br>13<br>~~1~~2<br>12<br>13<br>14<br>13<br>13<br>12<br>12<br>~~1~~1<br>11<br>11<br>13<br>12<br>12<br>12<br>11<br>14<br>1~~2~~<br>13<br>13<br>14<br>14<br>13<br>14<br>14<br>13<br>14<br>14<br>~~1~~5<br>13<br>13<br>13<br>13<br>13<br>1~~3~~<br>14|
|Bolillo bread|3<br>3<br>3<br>2<br>2<br>1<br>2<br>2<br>3<br>2<br>3<br>1<br>3<br>2<br>2<br>2<br>2<br>2<br>~~3~~<br>3<br>2<br>2<br>3<br>3<br>2<br>2<br>2<br>~~2~~<br>2<br>2<br>1<br>1<br>1<br>2<br>2<br>1<br>1<br>1<br>1<br>1<br>1<br>1<br>1<br>1<br>1|
|Concha bread<br>|5<br>5<br>5<br>5<br>5<br>5<br>4<br>6<br>5<br>4<br>5<br>4<br>5<br>4<br>5<br>5<br>5<br>4<br>4<br>4<br>4<br>5<br>4<br>4<br>4<br>4<br>4<br>~~4~~<br>5<br>3<br>4<br>5<br>5<br>4<br>3<br>6<br>3<br>4<br>5<br>4<br>4<br>4<br>5<br>4<br>5<br>5<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>|
|Corn tortillas|14<br>12<br>13<br>11<br>11<br>12<br>~~1~~2<br>12<br>14<br>12<br>~~1~~1<br>13<br>13<br>12<br>10<br>12<br>12<br>10<br>~~1~~1<br>12<br>11<br>10<br>11<br>10<br>11<br>11<br>11<br>1~~0~~<br>12<br>11<br>9<br>11<br>12<br>10<br>10<br>11<br>10<br>10<br>~~1~~2<br>10<br>10<br>11<br>13<br>12<br>1~~2~~<br>10|
|Water ‐ 1lt bottle|8<br>8<br>7<br>11<br>10<br>9<br>~~7~~<br>8<br>7<br>9<br>6<br>8<br>8<br>6<br>8<br>8<br>6<br>9<br>9<br>8<br>9<br>7<br>8<br>5<br>7<br>7<br>8<br>~~6~~<br>7<br>6<br>8<br>6<br>8<br>6<br>7<br>6<br>6<br>7<br>6<br>7<br>6<br>11<br>5<br>10<br>6<br>8|
|Water ‐ 1.5lt bottle<br>|5<br>7<br>6<br>5<br>5<br>6<br>7<br>6<br>7<br>5<br>4<br>5<br>5<br>6<br>5<br>6<br>6<br>6<br>7<br>5<br>6<br>5<br>5<br>~~5~~<br>5<br>5<br>5<br>7<br>6<br>5<br>8<br>6<br>5<br>6<br>5<br>5<br>6<br>5<br>5<br>6<br>5<br>6|
|Soda ‐ 2lt bottle|9<br>9<br>11<br>8<br>6<br>9<br>9<br>9<br>9<br>7<br>10<br>9<br>8<br>8<br>8<br>~~7~~<br>8<br>9<br>7<br>8<br>7<br>6<br>~~8~~<br>7<br>10<br>6<br>7<br>8<br>8<br>7<br>9<br>7<br>8<br>9<br>6<br>7<br>8<br>8|
|Soda ‐ 600ml bottle|15<br>15<br>16<br>15<br>15<br>15<br>~~1~~4<br>15<br>15<br>15<br>~~1~~4<br>15<br>15<br>13<br>14<br>14<br>14<br>15<br>~~1~~4<br>13<br>12<br>14<br>13<br>14<br>13<br>15<br>13<br>1~~2~~<br>13<br>13<br>14<br>14<br>14<br>13<br>13<br>16<br>14<br>15<br>~~1~~4<br>14<br>14<br>14<br>13<br>15<br>1~~3~~<br>14|
|Beef ‐ chop<br>|110 111 86<br>82<br>86 11~~2~~<br>~~9~~4 107 61<br>~~8~~6<br>64<br>78 103 72 106 89 12~~8~~<br>~~8~~6<br>94 101 88 103 75 104 82<br>93<br>9~~2~~<br>87 105 111 109 97 109 119 83 100 91<br>~~7~~9<br>95 109 117<br>85<br>86<br>9~~0 1~~03<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>|
|Beef ‐ ground|81<br>83<br>93<br>86<br>73<br>87<br>~~8~~2 102 92<br>81<br>~~7~~0<br>81<br>78<br>84<br>71<br>67<br>80<br>76<br>~~8~~5<br>89<br>81<br>86<br>78<br>77<br>82<br>79<br>91<br>8~~0~~<br>81<br>78<br>85<br>93<br>89<br>85<br>80<br>81<br>71<br>71<br>~~7~~8<br>78<br>88<br>84<br>75<br>86<br>7~~4~~<br>97|
|Beef ‐ rib|62<br>68<br>69<br>89<br>64<br>78<br>~~6~~9<br>68<br>86<br>60<br>~~6~~8<br>65<br>78<br>68<br>62<br>59<br>70 11~~9~~<br>~~9~~5<br>79<br>75<br>91<br>72<br>73<br>88<br>63<br>82<br>7~~0~~<br>72 101<br>84<br>88 104 111 92<br>66<br>66<br>57<br>~~6~~2<br>51<br>62<br>52<br>62<br>60<br>91|
|Beef ‐ steak|99 107 100<br>84<br>98<br>84<br>~~9~~6 102 105 10~~9 9~~2<br>89 103 104 90<br>90 101 10~~2~~<br>~~9~~8<br>96<br>98<br>99<br>96<br>92<br>98<br>98<br>99 1~~01 ~~97 106<br>90 113 105 102 93 103 102 91 ~~10~~5<br>97 107 93<br>95<br>97<br>9~~5 1~~03|
|Chicken ‐ whole|36<br>36<br>42<br>41<br>31<br>33<br>~~3~~5<br>36<br>31<br>32<br>~~3~~4<br>41<br>38<br>37<br>40<br>37<br>39<br>43<br>~~3~~3<br>40<br>36<br>37<br>38<br>39<br>32<br>37<br>37<br>3~~5~~<br>33<br>31<br>33<br>35<br>34<br>34<br>31<br>33<br>28<br>30<br>~~3~~2<br>30<br>36<br>34<br>32<br>36<br>3~~2~~<br>36|
|Chicken ‐ breast|62<br>85<br>91<br>70<br>68<br>~~6~~0<br>68<br>55<br>~~5~~9<br>54<br>51<br>52<br>59<br>56<br>59<br>~~5~~5<br>61<br>57<br>59<br>66<br>59<br>55<br>63<br>6~~2~~<br>57<br>52<br>56<br>62<br>59<br>68<br>66<br>63<br>47<br>~~5~~7<br>58<br>62<br>57<br>46<br>61<br>6~~0~~<br>63|
|Chicken ‐ roasted|89<br>85<br>97<br>75<br>85<br>98<br>~~8~~4 108 83<br>85 ~~10~~0 79<br>93<br>90<br>81<br>80<br>98<br>94<br>~~9~~2<br>72<br>78<br>89<br>86<br>87<br>70<br>76<br>76<br>8~~9~~<br>90<br>78<br>79<br>72<br>88<br>68<br>82<br>91<br>81<br>68<br>~~6~~9<br>65<br>67<br>63<br>98 104 7~~1~~<br>68|
|Pork ‐ rib|80<br>75<br>83<br>71<br>62<br>69<br>~~6~~8<br>75<br>70<br>88<br>~~8~~2<br>67<br>70<br>74<br>70<br>73<br>79<br>77<br>~~7~~2<br>60<br>72<br>89<br>74<br>75<br>74<br>74<br>82<br>8~~3~~<br>77<br>84<br>78<br>79<br>71<br>78<br>81<br>84<br>78<br>67<br>~~7~~2<br>80<br>80<br>83<br>80<br>75<br>7~~0~~<br>76|
|Pork ‐ steak|67<br>76<br>68<br>72<br>64<br>67<br>~~6~~4<br>65<br>69<br>72<br>~~6~~0<br>71<br>64<br>70<br>69<br>67<br>74<br>73<br>~~6~~8<br>65<br>70<br>81<br>72<br>76<br>69<br>72<br>76<br>6~~8~~<br>69<br>69<br>72<br>70<br>67<br>72<br>75<br>75<br>74<br>69<br>~~6~~7<br>66<br>79<br>70<br>61<br>71<br>6~~8~~<br>75|
|Apple|26<br>27<br>27<br>22<br>25<br>36<br>~~3~~1<br>33<br>28<br>~~2~~4<br>31<br>25<br>27<br>33<br>30<br>25<br>31<br>~~2~~9<br>31<br>29<br>28<br>27<br>31<br>30<br>32<br>2~~9~~<br>31<br>30<br>24<br>32<br>29<br>28<br>33<br>32<br>28<br>35<br>~~3~~1<br>30<br>30<br>34<br>31<br>35<br>3~~0~~<br>30|
|Banana|11<br>11<br>14<br>9<br>10<br>10<br>~~1~~0<br>11<br>11<br>11<br>9<br>10<br>10<br>9<br>11<br>10<br>9<br>9<br>8<br>9<br>9<br>10<br>11<br>8<br>10<br>10<br>11<br>1~~0~~<br>11<br>11<br>10<br>10<br>8<br>10<br>9<br>10<br>10<br>8<br>9<br>6<br>10<br>9<br>9<br>8<br>1~~0~~<br>11|
|Guava|24<br>23<br>23<br>23<br>20<br>24<br>~~1~~8<br>25<br>25<br>25<br>~~1~~9<br>21<br>19<br>17<br>18<br>23<br>18<br>19<br>~~1~~5<br>18<br>16<br>17<br>18<br>16<br>16<br>21<br>17<br>2~~2~~<br>17<br>15<br>15<br>18<br>14<br>15<br>18<br>16<br>16<br>18<br>~~1~~9<br>20<br>16<br>21<br>16<br>24<br>2~~0~~<br>18|
|Lime|16<br>16<br>16<br>14<br>14<br>15<br>~~1~~4<br>15<br>14<br>14<br>~~1~~4<br>13<br>14<br>14<br>12<br>15<br>14<br>13<br>~~1~~2<br>13<br>12<br>13<br>12<br>12<br>11<br>12<br>13<br>1~~2~~<br>13<br>13<br>13<br>13<br>13<br>12<br>12<br>12<br>12<br>13<br>~~1~~1<br>12<br>13<br>12<br>9<br>16<br>1~~2~~<br>14|
|Muskmelon<br>|14<br>14<br>15<br>14<br>12<br>13<br>~~1~~3<br>14<br>13<br>13<br>~~1~~2<br>13<br>11<br>11<br>13<br>14<br>13<br>12<br>~~1~~2<br>14<br>12<br>13<br>13<br>11<br>12<br>13<br>14<br>1~~2~~<br>15<br>14<br>12<br>16<br>15<br>13<br>15<br>15<br>12<br>13<br>~~1~~4<br>15<br>13<br>14<br>15<br>14<br>1~~4~~<br>15<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>|
|Orange|10<br>10<br>9<br>8<br>9<br>8<br>8<br>10<br>8<br>8<br>8<br>7<br>9<br>7<br>8<br>9<br>8<br>6<br>~~7~~<br>9<br>7<br>7<br>7<br>6<br>6<br>8<br>7<br>~~7~~<br>8<br>10<br>7<br>8<br>7<br>7<br>7<br>8<br>6<br>8<br>8<br>8<br>7<br>9<br>9<br>9<br>8<br>7|
|Papaya|20<br>20<br>20<br>19<br>18<br>18<br>~~1~~5<br>18<br>18<br>19<br>~~1~~7<br>19<br>18<br>17<br>17<br>17<br>17<br>17<br>~~1~~5<br>14<br>15<br>16<br>15<br>13<br>14<br>16<br>16<br>1~~4~~<br>13<br>14<br>13<br>15<br>14<br>14<br>14<br>13<br>11<br>13<br>~~1~~4<br>14<br>13<br>12<br>11<br>14<br>1~~5~~<br>15|
|Pear<br>|29<br>28<br>32<br>34<br>31<br>42<br>~~3~~2<br>31<br>27<br>27<br>~~3~~1<br>32<br>29<br>30<br>33<br>34<br>36<br>34<br>~~3~~2<br>33<br>30<br>32<br>28<br>33<br>31<br>32<br>35<br>3~~1~~<br>33<br>31<br>30<br>33<br>33<br>33<br>31<br>36<br>32<br>33<br>~~3~~5<br>33<br>33<br>31<br>34<br>34<br>3~~6~~<br>31<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>|
|Pineapple|16<br>14<br>13<br>13<br>13<br>12<br>~~1~~1<br>13<br>13<br>13<br>~~1~~2<br>12<br>11<br>11<br>11<br>12<br>11<br>13<br>~~1~~0<br>13<br>11<br>14<br>13<br>11<br>12<br>12<br>13<br>1~~2~~<br>12<br>14<br>13<br>12<br>14<br>12<br>13<br>12<br>12<br>12<br>~~1~~1<br>12<br>11<br>14<br>12<br>13<br>1~~3~~<br>13|
|Plantain|19<br>18<br>17<br>21<br>22<br>18<br>~~1~~3<br>19<br>19<br>~~2~~2<br>18<br>21<br>21<br>20<br>14<br>17<br>~~1~~8<br>14<br>17<br>16<br>18<br>14<br>15<br>18<br>16<br>1~~6~~<br>13<br>14<br>9<br>17<br>14<br>13<br>12<br>12<br>12<br>10<br>~~1~~4<br>12<br>13<br>11<br>13<br>12<br>1~~3~~<br>14|
|Watermelon|6<br>6<br>7<br>7<br>6<br>7<br>~~7~~<br>6<br>5<br>7<br>7<br>7<br>5<br>5<br>7<br>7<br>8<br>7<br>~~7~~<br>8<br>7<br>8<br>8<br>7<br>8<br>7<br>9<br>~~7~~<br>7<br>7<br>7<br>8<br>7<br>7<br>7<br>7<br>7<br>7<br>8<br>7<br>8<br>8<br>6<br>7<br>8<br>9|
|Avocado|36<br>35<br>36<br>30<br>30<br>33<br>~~3~~5<br>36<br>31<br>29<br>~~3~~2<br>34<br>31<br>28<br>32<br>34<br>32<br>31<br>~~3~~0<br>35<br>31<br>33<br>32<br>33<br>31<br>30<br>33<br>2~~7~~<br>35<br>36<br>32<br>36<br>35<br>33<br>31<br>34<br>30<br>34<br>~~3~~6<br>34<br>32<br>39<br>37<br>35<br>3~~0~~<br>35|
|Cabbage|9<br>9<br>7<br>5<br>7<br>6<br>7<br>7<br>7<br>6<br>5<br>4<br>6<br>4<br>6<br>5<br>7<br>6<br>8<br>7<br>6<br>6<br>6<br>7<br>8<br>6<br>6<br>~~6~~<br>6<br>6<br>6<br>7<br>6<br>6<br>13<br>6<br>7<br>6<br>6<br>7<br>6<br>6<br>5<br>7<br>7|
|Carrot|12<br>10<br>11<br>9<br>9<br>10<br>~~9~~<br>10<br>10<br>9<br>9<br>10<br>11<br>8<br>8<br>9<br>9<br>8<br>~~7~~<br>10<br>8<br>9<br>8<br>9<br>7<br>9<br>9<br>~~7~~<br>9<br>9<br>9<br>9<br>9<br>9<br>8<br>8<br>8<br>9<br>~~1~~0<br>9<br>9<br>10<br>9<br>10<br>1~~1~~<br>9|
|Chayote|14<br>13<br>14<br>15<br>16<br>16<br>~~1~~3<br>14<br>14<br>14<br>~~1~~5<br>14<br>16<br>14<br>14<br>15<br>12<br>15<br>~~1~~5<br>15<br>10<br>12<br>11<br>10<br>9<br>12<br>12<br>1~~2~~<br>11<br>13<br>9<br>11<br>10<br>10<br>10<br>8<br>8<br>7<br>~~1~~3<br>10<br>11<br>11<br>11<br>10<br>1~~1~~<br>11|
|Cucumber|13<br>12<br>12<br>13<br>12<br>12<br>~~1~~0<br>11<br>11<br>12<br>~~1~~2<br>13<br>13<br>11<br>13<br>14<br>12<br>12<br>~~1~~2<br>11<br>11<br>12<br>11<br>9<br>10<br>12<br>13<br>1~~2~~<br>12<br>10<br>11<br>12<br>12<br>12<br>10<br>10<br>10<br>11<br>~~1~~2<br>12<br>10<br>12<br>11<br>14<br>1~~2~~<br>12|
|Lettuce|10<br>11<br>12<br>7<br>9<br>9<br>9<br>10<br>9<br>10<br>9<br>9<br>10<br>6<br>8<br>8<br>7<br>~~8~~<br>10<br>7<br>7<br>8<br>11<br>8<br>7<br>8<br>~~7~~<br>8<br>9<br>8<br>8<br>8<br>8<br>8<br>9<br>6<br>8<br>~~1~~0<br>9<br>8<br>9<br>12<br>9<br>9<br>10|
|Onion<br>|12<br>12<br>15<br>13<br>13<br>13<br>~~1~~3<br>15<br>12<br>12<br>~~1~~2<br>13<br>12<br>10<br>13<br>12<br>13<br>11<br>~~1~~1<br>14<br>13<br>14<br>13<br>11<br>12<br>14<br>15<br>1~~2~~<br>15<br>14<br>13<br>13<br>12<br>13<br>12<br>13<br>11<br>13<br>~~1~~5<br>13<br>12<br>13<br>13<br>14<br>1~~6~~<br>13<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>|
|Jalapeno pepper|19<br>17<br>15<br>12<br>12<br>15<br>~~1~~6<br>16<br>16<br>19<br>~~1~~4<br>12<br>15<br>11<br>11<br>13<br>14<br>12<br>~~1~~5<br>19<br>14<br>18<br>16<br>27<br>18<br>15<br>15<br>1~~4~~<br>17<br>15<br>14<br>16<br>16<br>16<br>13<br>15<br>14<br>15<br>~~1~~8<br>15<br>16<br>15<br>19<br>1~~9~~<br>18|
|Poblano pepper|24<br>24<br>20<br>24<br>21<br>23<br>~~2~~0<br>21<br>23<br>23<br>~~1~~9<br>23<br>25<br>18<br>16<br>21<br>24<br>19<br>~~1~~7<br>22<br>19<br>22<br>20<br>18<br>19<br>20<br>21<br>1~~8~~<br>21<br>23<br>17<br>20<br>21<br>18<br>16<br>20<br>19<br>21<br>~~2~~7<br>25<br>20<br>22<br>24<br>25<br>2~~7~~<br>20|
|Serrano pepper|21<br>24<br>21<br>21<br>21<br>21<br>~~2~~1<br>22<br>19<br>20<br>~~1~~9<br>19<br>23<br>19<br>20<br>19<br>19<br>19<br>~~1~~9<br>24<br>19<br>24<br>22<br>20<br>20<br>21<br>22<br>1~~8~~<br>21<br>19<br>34<br>22<br>21<br>33<br>31<br>32<br>32<br>24<br>~~2~~8<br>25<br>21<br>22<br>25<br>25<br>2~~8~~<br>23|
|<br>Potato|11<br>13<br>18<br>15<br>10<br>17<br>~~1~~6<br>16<br>14<br>14<br>~~1~~4<br>15<br>16<br>12<br>15<br>15<br>15<br>14<br>~~1~~4<br>17<br>15<br>15<br>16<br>15<br>14<br>15<br>18<br>1~~4~~<br>16<br>15<br>15<br>15<br>15<br>16<br>13<br>14<br>13<br>15<br>~~1~~7<br>15<br>15<br>16<br>15<br>15<br>1~~6~~<br>15|
|Tomatillo|18<br>16<br>18<br>20<br>20<br>17<br>19<br>21<br>19<br>~~1~~9<br>20<br>20<br>19<br>16<br>15<br>19<br>13<br>~~1~~4<br>20<br>16<br>16<br>16<br>10<br>17<br>19<br>17<br>2~~0~~<br>17<br>18<br>9<br>13<br>14<br>15<br>14<br>17<br>15<br>18<br>~~1~~9<br>17<br>14<br>17<br>17<br>21<br>2~~0~~<br>14|
|Tomato ‐ beefsteak|18<br>20<br>19<br>18<br>16<br>19<br>~~2~~0<br>21<br>15<br>16<br>~~1~~7<br>17<br>17<br>13<br>19<br>15<br>19<br>19<br>~~1~~9<br>19<br>15<br>18<br>15<br>14<br>22<br>19<br>17<br>1~~8~~<br>20<br>18<br>19<br>21<br>20<br>18<br>17<br>23<br>19<br>17<br>~~1~~9<br>18<br>18<br>17<br>22<br>27<br>2~~2~~<br>20|
|Tomato ‐ roma|14<br>13<br>17<br>12<br>14<br>14<br>~~1~~3<br>12<br>13<br>13<br>~~1~~2<br>14<br>15<br>12<br>12<br>12<br>13<br>12<br>~~1~~2<br>14<br>15<br>14<br>14<br>11<br>12<br>14<br>13<br>1~~1~~<br>15<br>11<br>12<br>15<br>15<br>13<br>13<br>12<br>11<br>11<br>~~1~~5<br>13<br>13<br>14<br>14<br>13<br>1~~5~~<br>15|
|Zucchini|15<br>15<br>14<br>15<br>13<br>16<br>~~1~~9<br>20<br>13<br>14<br>~~1~~5<br>16<br>14<br>13<br>14<br>15<br>15<br>14<br>~~1~~4<br>17<br>13<br>15<br>14<br>12<br>14<br>15<br>15<br>1~~4~~<br>16<br>16<br>13<br>15<br>14<br>14<br>13<br>13<br>14<br>15<br>~~1~~8<br>18<br>14<br>17<br>14<br>18<br>1~~8~~<br>14|
|Salt<br>|9<br>10<br>10<br>8<br>8<br>~~7~~<br>10<br>10<br>5<br>8<br>8<br>7<br>7<br>7<br>10<br>6<br>8<br>8<br>8<br>7<br>8<br>7<br>6<br>6<br>7<br>~~9~~<br>7<br>8<br>7<br>8<br>7<br>8<br>6<br>6<br>9<br>6<br>7<br>7<br>6<br>6<br>4<br>8<br>6<br>7<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>|
|Sugar ‐ 1kg pack|19<br>17<br>15<br>16<br>17<br>15<br>~~1~~6<br>15<br>15<br>16<br>~~1~~7<br>16<br>16<br>16<br>16<br>16<br>22<br>~~1~~9<br>15<br>14<br>15<br>15<br>16<br>13<br>11<br>21<br>2~~0~~<br>21<br>16<br>19<br>16<br>22<br>17<br>16<br>14<br>13<br>13<br>14<br>16|
|Sugar ‐ 2kg pack|16<br>16<br>16<br>15<br>17<br>~~1~~5<br>17<br>17<br>~~1~~7<br>15<br>17<br>17<br>19<br>16<br>19<br>17<br>~~1~~8<br>22<br>18<br>19<br>17<br>12<br>16<br>15<br>16<br>1~~7~~<br>16<br>15<br>14<br>16<br>16<br>16<br>20<br>17<br>15<br>~~1~~5<br>15<br>13<br>14<br>16<br>15<br>1~~4~~<br>15|
|Cooking oil ‐ Mixed|28<br>28<br>28<br>23<br>24<br>22<br>~~2~~5<br>27<br>27<br>~~2~~5<br>26<br>27<br>26<br>27<br>22<br>23<br>24<br>~~2~~3<br>22<br>24<br>24<br>24<br>26<br>27<br>25<br>2~~5~~<br>25<br>24<br>22<br>24<br>24<br>21<br>24<br>23<br>22<br>22<br>~~2~~3<br>22<br>26<br>21<br>22<br>22<br>2~~2~~<br>24|
|<br>Cement ‐ 50kg bag|<br>146 141 179 114 132 12~~3 11~~4 135 157 15~~4 9~~9 114 120 102 104 118 128 10~~0 10~~6 115 100 124 113 109 112 110 113 1~~03 ~~120 115 107 108 109 104 98 118 111 11~~0 13~~9 117 104 117 136 125 13~~7 1~~17|

21
<u>Table 5. Average price dispersion in cities</u>

||<br><br>Northern border<br>Northwest<br>Northeast<br>Center north<br>Center south<br>South|
|---|---|
||MXL<br>TIJ<br>LAP<br>ACU<br>JUA<br>MAT<br>TPC<br>CUL<br>HMO<br>HUA<br>TOR<br>MVA<br>CHIH<br>JIM<br>DGO<br>MTY<br>TAM<br>FRE<br>AGS<br>COL<br>LEON<br>CTZ<br>GDL<br>TEP<br>MOR<br>JAC<br>QRO<br>SLP<br>ACA<br>IGU<br>TUL<br>TOL<br>CUE<br>PUE<br>TLAX<br>VER<br>COR<br>SAT<br>CAM<br>TAP<br>OAX<br>TEU<br>CHE<br>VSA<br>MID<br>MX|
|Beans<br>i|27<br>25<br>20<br>26<br>20<br>29<br>~~1~~6<br>19<br>24<br>32<br>~~2~~1<br>26<br>19<br>20<br>28<br>27<br>19<br>32<br>~~2~~7<br>20<br>23<br>22<br>21<br>18<br>17<br>13<br>18<br>3~~2~~<br>18<br>14<br>19<br>20<br>23<br>21<br>19<br>22<br>17<br>18<br>~~2~~3<br>18<br>17<br>13<br>13<br>21<br>1~~8~~<br>22<br>2<br>2<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>2~~2~~<br><br><br><br><br><br><br><br><br>2<br><br><br><br><br><br><br><br>|
|Rce|7<br>1<br>17<br>14<br>14<br>~~1~~5<br>8<br>15<br>6<br>~~1~~9<br>14<br>13<br>5<br>14<br>15<br>13<br>7<br>~~1~~0<br>15<br>10<br>4<br>15<br>11<br>8<br>9<br>15<br><br>6<br>8<br>17<br>10<br>14<br>15<br>11<br>14<br>1<br>17<br>~~1~~6<br>8<br>13<br>15<br>14<br>8<br>16|
|Eggs ‐ per piece|7<br>5<br>5<br>7<br>6<br>12<br>6<br>8<br>4<br>5<br>5<br>8<br>8<br>3<br>7<br>3<br>6<br>~~6~~<br>5<br>3<br>7<br>5<br>7<br>4<br>8<br>6<br>10<br>8<br>8|
|Eggs ‐ 12 pack|8<br>7<br>6<br>6<br>4<br>5<br>7<br>6<br>3<br>3<br>5<br>17<br>8<br>8<br>6<br>5<br>7|
|Eggs ‐ 18 pack|5<br>4<br>6<br>6<br>5<br>6<br>8<br>5<br>10<br>7|
|Eggs ‐ 30 pack|8<br>6<br>7<br>7<br>10<br>11<br>12<br>13<br>4<br>8<br>8<br>5<br>~~4~~<br>6<br>8<br>10<br>7<br>3<br>14<br>8|
|Milk|9<br>5<br>10<br>14<br>7<br>8<br>8<br>8<br>8<br>11<br>~~1~~3<br>15<br>5<br>5<br>5<br>15<br>10<br>9<br>9<br>8<br>4<br>9<br>13<br>12<br>9<br>8<br>1~~0~~<br>5<br>6<br>5<br>6<br>8<br>8<br>7<br>13<br>9<br>12<br>4<br>8<br>8<br>6<br>10<br>1~~0~~<br>7|
|Bolillo bread|18<br>27<br>42<br>35<br>45<br>8<br>~~2~~7<br>40<br>38<br>25<br>~~4~~5<br>11<br>38<br>34<br>15<br>35<br>20<br>30<br>~~1~~3<br>42<br>22<br>21<br>36<br>45<br>32<br>33<br>15<br>2~~6~~<br>24<br>33<br>10<br>8<br>23<br>20<br>13<br>0<br>0<br>35<br>26<br>22<br>2<br>12<br>2~~6~~<br>10|
|Concha bread|23<br>14<br>8<br>12<br>10<br>14<br>~~2~~0<br>19<br>21<br>20<br>5<br>21<br>9<br>14<br>5<br>12<br>14<br>7<br>~~1~~3<br>13<br>18<br>10<br>15<br>7<br>22<br>16<br>15<br>1~~1~~<br>13<br>16<br>16<br>10<br>12<br>18<br>14<br>13<br>29<br>10<br>~~2~~5<br>22<br>19<br>11<br>14<br>15<br>1~~5~~<br>10|
|Corn tortillas|14<br>12<br>16<br>15<br>15<br>15<br>~~1~~2<br>11<br>18<br>18<br>~~1~~1<br>16<br>14<br>13<br>10<br>12<br>13<br>12<br>~~1~~4<br>13<br>9<br>13<br>12<br>13<br>9<br>14<br>16<br>1~~0~~<br>12<br>18<br>5<br>11<br>19<br>13<br>8<br>18<br>12<br>13<br>~~1~~6<br>10<br>14<br>15<br>21<br>16<br>1~~6~~<br>8|
|Water ‐ 1lt bottle|22<br>9<br>7<br>2<br>11<br>7<br>~~1~~2<br>26<br>17<br>20<br>13<br>20<br>18<br>9<br>~~7~~<br>25<br>8<br>18<br>12<br>14<br>10<br>1~~1~~<br>6<br>16<br>10<br>11<br>8<br>29<br>2~~3~~<br>16|
|Water ‐ 1.5lt bottle|4<br>13<br>~~2~~<br>12<br>~~1~~2<br>7<br>10<br>8<br>6<br>7<br>4<br>~~1~~5<br>20<br>14<br>16<br>7<br>13<br>13<br>~~7~~<br>0<br>7<br>8<br>17<br>12<br>18<br>25<br>17<br>10<br>4<br>14<br>23<br>7<br>10<br>6<br>14|
|Soda ‐ 2lt bottle|11<br>7<br>25<br>11<br>~~1~~1<br>13<br>7<br>10<br>6<br>8<br>8<br>4<br>13<br>~~7~~<br>16<br>14<br>8<br>8<br>7<br>1~~3~~<br>7<br>11<br>5<br>12<br>16<br>~~1~~4<br>19<br>6<br>17|
|Soda ‐ 600ml bottle|3<br>10<br>11<br>2<br>3<br>5<br>~~1~~3<br>3<br>3<br>4<br>9<br>5<br>5<br>7<br>3<br>9<br>4<br>2<br>8<br>7<br>4<br>12<br>9<br>11<br>5<br>9<br>~~4~~<br>7<br>7<br>7<br>4<br>5<br>7<br>1<br>5<br>9<br>13<br>~~1~~1<br>9<br>0<br>10<br>8<br>14<br>8<br>9|
|Beef ‐ chop|19<br>9<br>13<br>18<br>2<br>~~2~~0<br>4<br>18<br>15<br>9<br>~~1~~1<br>3<br>13<br>4<br>9<br>14<br>4<br>6<br>1~~3~~<br>6<br>6<br>4<br>8<br>5<br>9<br>30<br>18<br>22<br>~~2~~1<br>23<br>12<br>18<br>5<br>2~~4~~<br>17|
|Beef ‐ ground|16<br>18<br>13<br>22<br>34<br>27<br>~~1~~4<br>7<br>26<br>14<br>~~2~~3<br>21<br>19<br>24<br>33<br>31<br>20<br>17<br>~~1~~5<br>16<br>16<br>17<br>25<br>7<br>16<br>11<br>20<br>1~~6~~<br>12<br>13<br>9<br>16<br>9<br>17<br>13<br>24<br>20<br>10<br>~~1~~8<br>20<br>19<br>7<br>6<br>20<br>1~~9~~<br>11|
|Beef ‐ rib|28<br>17<br>12<br>5<br>32<br>24<br>~~3~~3<br>7<br>7<br>10<br>~~1~~9<br>19<br>23<br>8<br>6<br>14<br>18<br>~~2~~5<br>35<br>18<br>23<br>6<br>27<br>42<br>4<br>18<br>4<br>13<br>12<br>4<br>8<br>23<br>8<br>6<br>11<br>23|
|Beef ‐ steak|12<br>8<br>12<br>23<br>12<br>21<br>~~1~~2<br>5<br>17<br>14<br>~~2~~1<br>25<br>18<br>10<br>14<br>22<br>14<br>13<br>~~1~~1<br>9<br>12<br>7<br>10<br>10<br>12<br>11<br>12<br>1~~0~~<br>9<br>10<br>3<br>10<br>8<br>9<br>5<br>12<br>12<br>13<br>~~1~~3<br>20<br>15<br>9<br>12<br>14<br>1~~6~~<br>8|
|Chicken ‐ whole|10<br>10<br>22<br>18<br>11<br>14<br>~~7~~<br>13<br>10<br>6<br>~~1~~1<br>12<br>14<br>13<br>20<br>11<br>20<br>12<br>~~1~~0<br>10<br>11<br>15<br>10<br>14<br>11<br>10<br>15<br>1~~1~~<br>11<br>8<br>7<br>13<br>10<br>11<br>8<br>16<br>7<br>7<br>~~1~~1<br>6<br>17<br>12<br>11<br>11<br>1~~1~~<br>10|
|Chicken ‐ breast|12<br>12<br>~~2~~8<br>~~1~~9<br>8<br>17<br>11<br>10<br>13<br>~~2~~0<br>15<br>15<br>19<br>5<br>7<br>25<br>1~~0~~<br>14<br>12<br>3<br>6<br>20<br>6<br>11<br>12<br>9<br>10<br>2~~1~~<br>10|
|Chicken ‐ roasted|13<br>15<br>22<br>16<br>24<br>8<br>9<br>13<br>4<br>2<br>~~2~~1<br>11<br>23<br>19<br>19<br>28<br>7<br>6<br>~~1~~7<br>14<br>13<br>16<br>22<br>16<br>23<br>13<br>2~~1~~<br>25<br>14<br>5<br>19<br>18<br>9<br>23<br>24<br>30<br>5<br>9<br>7<br>36<br>30<br>1~~1~~<br>19|
|Pork ‐ rib|19<br>20<br>19<br>17<br>24<br>21<br>~~1~~9<br>16<br>27<br>9<br>~~1~~9<br>32<br>19<br>16<br>17<br>22<br>19<br>13<br>~~1~~4<br>17<br>19<br>8<br>18<br>11<br>17<br>11<br>10<br>2~~2~~<br>12<br>9<br>15<br>16<br>11<br>14<br>6<br>12<br>13<br>18<br>~~1~~8<br>15<br>17<br>6<br>10<br>19<br>2~~1~~<br>19|
|Pork ‐ steak|11<br>11<br>12<br>4<br>14<br>10<br>~~1~~2<br>11<br>12<br>6<br>~~1~~6<br>11<br>15<br>7<br>14<br>14<br>8<br>9<br>8<br>10<br>11<br>9<br>12<br>3<br>12<br>6<br>6<br>~~8~~<br>6<br>5<br>4<br>5<br>8<br>9<br>9<br>10<br>6<br>7<br>21<br>9<br>5<br>9<br>10<br>8<br>10|
|Apple|12<br>9<br>7<br>9<br>36<br>19<br>~~1~~0<br>11<br>9<br>~~1~~6<br>14<br>29<br>11<br>27<br>16<br>~~1~~2<br>6<br>12<br>9<br>27<br>7<br>10<br>9<br>~~8~~<br>20<br>15<br>8<br>16<br>14<br>18<br>4<br>~~2~~1<br>10<br>12<br>5<br>11<br>1~~3~~<br>15|
|Banana|18<br>16<br>11<br>12<br>15<br>17<br>~~2~~6<br>29<br>23<br>25<br>~~2~~0<br>28<br>19<br>10<br>19<br>22<br>22<br>17<br>~~1~~7<br>27<br>17<br>18<br>29<br>5<br>33<br>23<br>33<br>2~~0~~<br>18<br>20<br>10<br>16<br>18<br>20<br>10<br>41<br>30<br>13<br>~~1~~2<br>27<br>16<br>11<br>14<br>26<br>3~~3~~<br>25|
|Guava|12<br>12<br>12<br>11<br>10<br>9<br>~~2~~0<br>16<br>15<br>15<br>~~2~~4<br>23<br>17<br>12<br>24<br>15<br>12<br>29<br>~~1~~9<br>27<br>17<br>18<br>23<br>6<br>29<br>8<br>14<br>1~~2~~<br>17<br>17<br>7<br>19<br>18<br>22<br>8<br>15<br>11<br>10<br>~~1~~9<br>12<br>9<br>8<br>20<br>13<br>2~~0~~<br>27|
|Lime<br>|18<br>16<br>19<br>17<br>18<br>14<br>~~1~~6<br>14<br>13<br>11<br>~~1~~7<br>18<br>18<br>17<br>18<br>20<br>17<br>16<br>~~1~~8<br>16<br>19<br>12<br>19<br>14<br>19<br>14<br>15<br>1~~9~~<br>23<br>12<br>13<br>20<br>16<br>25<br>11<br>17<br>14<br>4<br>~~3~~3<br>17<br>15<br>26<br>21<br>19<br>2~~0~~<br>18<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>|
|Muskmelon|19<br>16<br>20<br>13<br>24<br>18<br>~~1~~3<br>16<br>20<br>15<br>~~2~~7<br>20<br>24<br>18<br>21<br>18<br>18<br>12<br>~~1~~9<br>18<br>18<br>14<br>18<br>11<br>20<br>11<br>17<br>2~~2~~<br>19<br>18<br>15<br>17<br>10<br>22<br>14<br>13<br>19<br>12<br>~~1~~6<br>13<br>15<br>12<br>13<br>21<br>2~~2~~<br>17|
|Orange|21<br>17<br>19<br>19<br>22<br>24<br>~~1~~9<br>16<br>30<br>16<br>~~2~~0<br>23<br>19<br>15<br>21<br>20<br>21<br>32<br>~~2~~8<br>18<br>18<br>27<br>26<br>11<br>27<br>12<br>15<br>2~~1~~<br>19<br>18<br>16<br>24<br>27<br>27<br>18<br>17<br>24<br>18<br>~~2~~1<br>20<br>17<br>19<br>17<br>19<br>2~~8~~<br>27|
|Papaya|19<br>15<br>12<br>17<br>18<br>20<br>~~2~~6<br>19<br>15<br>11<br>~~2~~3<br>18<br>20<br>14<br>21<br>23<br>21<br>19<br>~~2~~4<br>32<br>14<br>17<br>24<br>12<br>25<br>24<br>12<br>2~~9~~<br>23<br>17<br>14<br>17<br>19<br>24<br>13<br>26<br>21<br>15<br>~~1~~3<br>15<br>17<br>24<br>28<br>22<br>2~~3~~<br>17|
|Pear|12<br>9<br>13<br>19<br>13<br>~~1~~4<br>14<br>17<br>10<br>~~1~~7<br>12<br>18<br>10<br>13<br>16<br>13<br>8<br>~~1~~3<br>14<br>10<br>10<br>19<br>7<br>10<br>6<br>11<br>1~~5~~<br>12<br>10<br>9<br>14<br>11<br>13<br>10<br>11<br>7<br>~~1~~2<br>10<br>12<br>9<br>1~~2~~<br>14|
|Pineapple|11<br>16<br>13<br>9<br>14<br>17<br>~~1~~6<br>13<br>14<br>11<br>~~1~~9<br>17<br>21<br>11<br>20<br>24<br>14<br>5<br>~~1~~9<br>13<br>15<br>12<br>17<br>10<br>15<br>5<br>15<br>1~~2~~<br>10<br>19<br>33<br>12<br>17<br>14<br>7<br>13<br>11<br>~~1~~1<br>15<br>16<br>2~~0~~<br>11|
|Plantain|8<br>13<br>20<br>11<br>13<br>7<br>7<br>10<br>~~1~~8<br>7<br>12<br>8<br>5<br>8<br>5<br>9<br>14<br>9<br>12<br>18<br>~~1~~4<br>15<br>7<br>14<br>8<br>1~~1~~<br>15|
|Watermelon|29<br>18<br>20<br>18<br>27<br>20<br>~~2~~7<br>22<br>36<br>19<br>~~2~~0<br>25<br>28<br>20<br>18<br>19<br>18<br>19<br>~~1~~9<br>17<br>15<br>12<br>20<br>12<br>16<br>11<br>17<br>1~~8~~<br>16<br>13<br>11<br>17<br>13<br>18<br>16<br>17<br>13<br>12<br>~~1~~4<br>18<br>15<br>13<br>31<br>20<br>2~~1~~<br>19|
|Avocado|17<br>13<br>18<br>17<br>16<br>19<br>~~1~~7<br>14<br>18<br>17<br>~~1~~5<br>18<br>17<br>10<br>14<br>21<br>16<br>8<br>~~1~~5<br>14<br>15<br>9<br>16<br>7<br>12<br>10<br>14<br>2~~2~~<br>13<br>14<br>12<br>15<br>14<br>15<br>8<br>17<br>13<br>17<br>~~1~~8<br>16<br>13<br>8<br>12<br>17<br>2~~4~~<br>15|
|Cabbage|15<br>9<br>30<br>21<br>29<br>21<br>~~1~~8<br>7<br>16<br>12<br>~~1~~8<br>60<br>13<br>23<br>31<br>36<br>14<br>~~3~~2<br>26<br>22<br>19<br>32<br>23<br>15<br>1~~3~~<br>12<br>38<br>7<br>11<br>10<br>7<br>31<br>16<br>~~1~~4<br>26<br>14<br>27<br>1~~0~~<br>28|
|Carrot|13<br>20<br>16<br>19<br>17<br>~~1~~9<br>12<br>18<br>13<br>~~1~~8<br>19<br>13<br>20<br>20<br>19<br>19<br>12<br>~~2~~5<br>15<br>19<br>12<br>20<br>15<br>24<br>8<br>16<br>2~~5~~<br>16<br>16<br>12<br>18<br>14<br>23<br>12<br>18<br>16<br>9<br>~~1~~4<br>13<br>15<br>14<br>10<br>16<br>1~~9~~<br>22|
|Chayote|14<br>19<br>21<br>13<br>18<br>13<br>~~1~~5<br>15<br>14<br>10<br>~~2~~0<br>27<br>13<br>13<br>27<br>18<br>17<br>20<br>~~2~~4<br>17<br>18<br>11<br>25<br>15<br>29<br>8<br>22<br>1~~9~~<br>14<br>24<br>8<br>20<br>14<br>19<br>5<br>24<br>28<br>13<br>~~1~~6<br>15<br>17<br>12<br>12<br>24<br>1~~8~~<br>23|
|Cucumber|19<br>16<br>18<br>9<br>16<br>12<br>~~1~~5<br>17<br>21<br>18<br>~~1~~6<br>19<br>14<br>12<br>16<br>15<br>18<br>20<br>~~1~~8<br>15<br>19<br>7<br>14<br>12<br>19<br>7<br>15<br>1~~3~~<br>14<br>13<br>11<br>17<br>11<br>16<br>9<br>24<br>19<br>9<br>~~1~~7<br>15<br>15<br>13<br>31<br>14<br>2~~2~~<br>23|
|Lettuce|12<br>20<br>20<br>11<br>13<br>21<br>~~1~~2<br>16<br>16<br>13<br>19<br>16<br>8<br>17<br>20<br>~~3~~5<br>15<br>19<br>13<br>17<br>8<br>28<br>2~~1~~<br>17<br>18<br>12<br>9<br>10<br>19<br>21<br>11<br>6<br>~~1~~8<br>5<br>21<br>16<br>7<br>13<br>1~~4~~<br>24|
|Onion|19<br>22<br>21<br>19<br>24<br>20<br>~~2~~0<br>22<br>27<br>25<br>~~2~~4<br>26<br>23<br>23<br>28<br>25<br>22<br>23<br>~~2~~6<br>22<br>28<br>22<br>32<br>20<br>36<br>24<br>35<br>2~~9~~<br>22<br>29<br>26<br>24<br>24<br>26<br>19<br>28<br>28<br>22<br>~~1~~7<br>24<br>15<br>16<br>20<br>29<br>2~~8~~<br>28|
|Jalapeno pepper|9<br>8<br>16<br>9<br>20<br>13<br>~~1~~8<br>20<br>15<br>~~1~~8<br>11<br>13<br>17<br>12<br>21<br>18<br>~~1~~6<br>9<br>12<br>9<br>16<br>8<br>11<br>1~~9~~<br>16<br>23<br>11<br>21<br>21<br>24<br>6<br>14<br>9<br>13<br>~~1~~7<br>18<br>12<br>12<br>12<br>20|
|Poblano pepper|22<br>22<br>18<br>12<br>23<br>14<br>~~1~~5<br>17<br>16<br>14<br>~~2~~5<br>16<br>13<br>22<br>32<br>20<br>14<br>21<br>~~2~~4<br>16<br>21<br>13<br>20<br>11<br>19<br>10<br>17<br>2~~1~~<br>17<br>14<br>18<br>20<br>21<br>27<br>8<br>16<br>19<br>11<br>~~1~~6<br>15<br>18<br>12<br>15<br>14<br>1~~7~~<br>22|
|<br>Serrano pepper|22<br>18<br>19<br>17<br>21<br>18<br>~~1~~9<br>17<br>16<br>19<br>~~2~~6<br>21<br>18<br>26<br>23<br>22<br>22<br>22<br>~~2~~3<br>19<br>21<br>11<br>17<br>14<br>18<br>13<br>20<br>3~~0~~<br>21<br>25<br>7<br>21<br>23<br>22<br>22<br>23<br>23<br>14<br>~~1~~9<br>13<br>18<br>17<br>17<br>21<br>1~~8~~<br>21|
|Potato|29<br>30<br>15<br>18<br>25<br>17<br>~~1~~3<br>17<br>22<br>21<br>~~1~~8<br>22<br>22<br>15<br>24<br>22<br>20<br>12<br>~~2~~1<br>16<br>21<br>16<br>24<br>9<br>23<br>20<br>22<br>2~~1~~<br>16<br>22<br>21<br>20<br>25<br>24<br>21<br>20<br>24<br>11<br>~~1~~4<br>17<br>13<br>14<br>18<br>24<br>1~~9~~<br>21|
|Tomatillo|21<br>28<br>19<br>13<br>23<br>24<br>21<br>14<br>18<br>~~1~~7<br>15<br>19<br>29<br>30<br>21<br>28<br>~~3~~6<br>8<br>12<br>21<br>23<br>19<br>19<br>7<br>15<br>1~~3~~<br>18<br>10<br>27<br>29<br>26<br>27<br>20<br>22<br>10<br>~~1~~3<br>15<br>18<br>19<br>19<br>18<br>1~~7~~<br>29|
|Tomato ‐ beefsteak|13<br>14<br>18<br>20<br>16<br>~~1~~5<br>16<br>24<br>10<br>~~1~~8<br>23<br>16<br>11<br>27<br>19<br>~~1~~5<br>16<br>18<br>10<br>26<br>12<br>24<br>12<br>15<br>1~~5~~<br>18<br>12<br>21<br>10<br>12<br>22<br>7<br>~~1~~4<br>13<br>12<br>10<br>8<br>1~~4~~<br>21|
|Tomato ‐ roma|28<br>27<br>21<br>23<br>26<br>25<br>~~1~~9<br>33<br>25<br>21<br>~~2~~6<br>24<br>24<br>17<br>27<br>31<br>23<br>19<br>~~2~~6<br>20<br>21<br>16<br>24<br>17<br>24<br>18<br>21<br>3~~2~~<br>18<br>24<br>10<br>18<br>23<br>27<br>18<br>22<br>17<br>20<br>~~1~~6<br>14<br>17<br>10<br>18<br>24<br>2~~2~~<br>20|
|Zucchini|23<br>19<br>21<br>23<br>28<br>17<br>~~1~~8<br>20<br>25<br>18<br>~~2~~2<br>21<br>20<br>14<br>24<br>22<br>19<br>20<br>~~2~~6<br>17<br>21<br>14<br>26<br>15<br>25<br>13<br>22<br>2~~4~~<br>20<br>16<br>21<br>20<br>21<br>24<br>14<br>24<br>26<br>14<br>~~2~~2<br>20<br>24<br>13<br>35<br>17<br>2~~8~~<br>24|
|Salt<br>|13<br>15<br>14<br>4<br>6<br>15<br>~~1~~0<br>10<br>5<br>22<br>6<br>~~1~~2<br>8<br>9<br>17|
|Sugar ‐ 1kg pack|9<br>14<br>7<br>8<br>13<br>8<br>~~7~~<br>7<br>5<br>5<br>~~1~~9<br>10<br>8<br>10<br>9<br>10<br>17<br>16<br>14<br>9<br>11<br>3<br>~~9~~<br>8<br>5<br>2<br>1<br>14<br>3<br>16<br>8|
|Sugar ‐ 2kg pack|10<br>6<br>7<br>10<br>11<br>12<br>9<br>11<br>12<br>9<br>14<br>~~1~~0<br>11<br>11<br>22<br>7<br>1~~5~~<br>8<br>7<br>25<br>7<br>10<br>12<br>16<br>8<br>~~1~~2<br>8<br>9<br>6<br>8<br>7<br>1~~8~~<br>15|
|Cooking oil ‐ Mixed|7<br>7<br>10<br>3<br>3<br>6<br>12<br>2<br>5<br>6<br>5<br>4<br>3<br>6<br>8<br>4<br>7<br>3<br>5<br>5<br>6<br>11<br>8<br>5<br>~~1~~1<br>7<br>12<br>7<br>5<br>5<br>8|
|Cement ‐ 50kg bag|<br>1<br>1<br>1<br>1<br>2<br>2<br>2<br>3<br>3<br>2<br>2<br>~~9~~<br>3<br>8<br>6<br>6|

22
<u>Table 6. Average price volatility in cities</u>

||<br>Northern border<br>Northwest<br>Northeast<br>Center north<br>Center south<br>South<br>|
|---|---|
||MXL<br>TIJ<br>LAP<br>ACU<br>JUA<br>MAT<br>TPC<br>CUL<br>HMO<br>HUA<br>TOR<br>MVA<br>CHIH<br>JIM<br>DGO<br>MTY<br>TAM<br>FRE<br>AGS<br>COL<br>LEON<br>CTZ<br>GDL<br>TEP<br>MOR<br>JAC<br>QRO<br>SLP<br>ACA<br>IGU<br>TUL<br>TOL<br>CUE<br>PUE<br>TLAX<br>VER<br>COR<br>SAT<br>CAM<br>TAP<br>OAX<br>TEU<br>CHE<br>VSA<br>MID<br>MX|
|Beans<br>|6<br>7<br>7<br>7<br>6<br>6<br>6<br>6<br>7<br>5<br>8<br>5<br>8<br>8<br>6<br>6<br>7<br>6<br>6<br>6<br>5<br>6<br>7<br>5<br>6<br>6<br>7<br>6<br>~~4~~<br>3<br>4<br>5<br>5<br>4<br>4<br>5<br>3<br>4<br>6<br>6<br>6<br>5<br>4<br>5<br>~~5~~<br>5<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>|
|Rice|4<br>6<br>2<br>9<br>5<br>3<br>4<br>9<br>4<br>4<br>3<br>6<br>4<br>5<br>5<br>4<br>5<br>3<br>8<br>6<br>3<br>5<br>4<br>4<br>5<br>6<br>5<br>7<br>~~5~~<br>9<br>3<br>3<br>2<br>3<br>3<br>6<br>3<br>3<br>6<br>7<br>2<br>4<br>8<br>5<br>~~4~~<br>4|
|Eggs ‐ per piece|2<br>4<br>9<br>6<br>6<br>8<br>5<br>5<br>6<br>7<br>5<br>8<br>5<br>8<br>6<br>5<br>7<br>4<br>7<br>9<br>9<br>7<br>8<br>6<br>4<br>5<br>7<br>7<br>6<br>6<br>6<br>~~3~~<br>6|
|Eggs ‐ 12 pack<br>|4<br>10<br>9<br>5<br>7<br>6<br>10<br>4<br>7<br>8<br>3<br>4<br>7<br>6<br>6<br>13<br>5<br>3<br>~~7~~<br>6<br>6<br>6<br>7<br>8<br>8<br>6<br>6<br>3<br>9<br>18<br>10<br>~~4~~<br>6<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>|
|Eggs ‐ 18 pack|1<br>11<br>5<br>7<br>4<br>5<br>6<br>8<br>7<br>9<br>5<br>3<br>8<br>5<br>13<br>~~9~~<br>10<br>3<br>11<br>9<br>8<br>10<br>8<br>5<br>6<br>5<br>6<br>1<br>4<br>7<br>7|
|Eggs ‐ 30 pack|8<br>8<br>9<br>9<br>8<br>8<br>8<br>7<br>5<br>6<br>6<br>8<br>10<br>11<br>7<br>6<br>8<br>2<br>2<br>5<br>9<br>8<br>~~6~~<br>3<br>7<br>8<br>8<br>7<br>6<br>9<br>9<br>7<br>5<br>6<br>~~9~~<br>6|
|Milk|1<br>1<br>2<br>0<br>2<br>2<br>1<br>1<br>1<br>3<br>1<br>1<br>2<br>1<br>1<br>1<br>2<br>1<br>1<br>1<br>1<br>1<br>2<br>1<br>2<br>1<br>1<br>1<br>~~1~~<br>1<br>1<br>1<br>1<br>2<br>1<br>2<br>1<br>1<br>1<br>2<br>2<br>2<br>2<br>1<br>~~2~~<br>1|
|Bolillo bread<br>|2<br>1<br>2<br>1<br>2<br>2<br>3<br>2<br>3<br>1<br>1<br>1<br>1<br>2<br>1<br>2<br>1<br>1<br>1<br>1<br>2<br>1<br>1<br>1<br>1<br>1<br>1<br>1<br>~~2~~<br>1<br>0<br>1<br>1<br>0<br>1<br>2<br>0<br>2<br>3<br>3<br>1<br>2<br>2<br>~~2~~<br>2<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>|
|Concha bread|1<br>2<br>3<br>3<br>5<br>3<br>2<br>1<br>3<br>2<br>2<br>4<br>2<br>1<br>2<br>2<br>3<br>3<br>1<br>2<br>2<br>1<br>2<br>1<br>1<br>1<br>2<br>2<br>~~4~~<br>3<br>3<br>2<br>3<br>3<br>2<br>2<br>2<br>2<br>2<br>3<br>4<br>2<br>2<br>3<br>~~2~~<br>3|
|Corn tortillas|1<br>2<br>2<br>3<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>1<br>1<br>1<br>2<br>2<br>~~2~~<br>2<br>1<br>2<br>2<br>2<br>2<br>3<br>3<br>2<br>2<br>3<br>2<br>2<br>2<br>2<br>~~2~~<br>2|
|Water ‐ 1lt bottle|5<br>1<br>6<br>2<br>2<br>2<br>5<br>4<br>4<br>1<br>4<br>2<br>4<br>8<br>5<br>4<br>10<br>2<br>1<br>0<br>2<br>4<br>2<br>0<br>3<br>2<br>2<br>10<br>~~0~~<br>10<br>1<br>15<br>4<br>4<br>10<br>12<br>4<br>1<br>12<br>5<br>14<br>2<br>9<br>4<br>~~4~~<br>3|
|Water ‐ 1.5lt bottle|5<br>1<br>4<br>1<br>3<br>2<br>2<br>3<br>1<br>2<br>1<br>4<br>4<br>1<br>1<br>1<br>3<br>3<br>1<br>1<br>3<br>6<br>6<br>2<br>~~7~~<br>2<br>3<br>2<br>2<br>4<br>4<br>1<br>5<br>0<br>4<br>4<br>8<br>3<br>3<br>6<br>~~3~~<br>5|
|Soda ‐ 2lt bottle|4<br>5<br>1<br>8<br>3<br>1<br>3<br>2<br>3<br>7<br>6<br>4<br>7<br>2<br>5<br>1<br>4<br>1<br>2<br>0<br>8<br>4<br>1<br>~~4~~<br>1<br>4<br>2<br>1<br>4<br>1<br>1<br>6<br>2<br>1<br>7<br>5<br>~~7~~<br>5|
|Soda ‐ 600ml bottle|1<br>3<br>1<br>1<br>3<br>1<br>2<br>1<br>2<br>1<br>2<br>1<br>1<br>2<br>1<br>2<br>1<br>1<br>1<br>1<br>2<br>1<br>2<br>1<br>1<br>1<br>1<br>1<br>~~1~~<br>4<br>4<br>1<br>2<br>2<br>1<br>1<br>1<br>1<br>2<br>1<br>1<br>1<br>2<br>2<br>~~4~~<br>2|
|Beef ‐ chop|4<br>1<br>6<br>4<br>4<br>8<br>1<br>3<br>7<br>7<br>3<br>2<br>1<br>6<br>4<br>12<br>2<br>3<br>1<br>2<br>4<br>2<br>2<br>3<br>2<br>3<br>5<br>~~1~~<br>4<br>3<br>5<br>1<br>4<br>2<br>3<br>3<br>2<br>5<br>2<br>4<br>3<br>7<br>2<br>~~6~~<br>4|
|Beef ‐ ground|4<br>5<br>4<br>7<br>4<br>4<br>3<br>3<br>3<br>5<br>5<br>5<br>3<br>5<br>3<br>3<br>7<br>5<br>7<br>3<br>3<br>3<br>5<br>3<br>4<br>5<br>3<br>6<br>~~7~~<br>6<br>4<br>5<br>5<br>5<br>4<br>5<br>5<br>6<br>6<br>4<br>6<br>4<br>4<br>3<br>~~5~~<br>4|
|Beef ‐ rib|4<br>4<br>5<br>6<br>5<br>5<br>5<br>7<br>2<br>8<br>7<br>6<br>6<br>2<br>10<br>4<br>5<br>2<br>2<br>4<br>3<br>5<br>4<br>2<br>2<br>3<br>4<br>5<br>~~4~~<br>2<br>2<br>1<br>4<br>2<br>1<br>6<br>5<br>7<br>3<br>6<br>5<br>2<br>2<br>4<br>4|
|Beef ‐ steak|3<br>3<br>4<br>4<br>5<br>5<br>3<br>4<br>4<br>3<br>6<br>3<br>5<br>2<br>4<br>4<br>5<br>3<br>2<br>3<br>2<br>3<br>2<br>2<br>3<br>2<br>3<br>4<br>~~5~~<br>5<br>2<br>4<br>3<br>3<br>3<br>2<br>4<br>3<br>3<br>5<br>5<br>2<br>4<br>4<br>~~4~~<br>3|
|Chicken ‐ whole|5<br>7<br>5<br>5<br>8<br>8<br>4<br>5<br>8<br>3<br>4<br>3<br>5<br>5<br>6<br>5<br>7<br>3<br>6<br>3<br>6<br>7<br>5<br>5<br>9<br>6<br>6<br>6<br>~~10~~<br>13<br>5<br>7<br>6<br>7<br>8<br>5<br>4<br>8<br>8<br>11<br>8<br>8<br>7<br>6<br>~~9~~<br>6|
|Chicken ‐ breast|8<br>7<br>1<br>6<br>3<br>2<br>4<br>1<br>6<br>1<br>7<br>1<br>1<br>5<br>5<br>8<br>1<br>6<br>3<br>4<br>3<br>7<br>3<br>11<br>~~7~~<br>1<br>3<br>9<br>4<br>8<br>7<br>3<br>4<br>11<br>10<br>5<br>9<br>15<br>2<br>~~5~~<br>7|
|Chicken ‐ roasted|1<br>2<br>1<br>3<br>2<br>1<br>1<br>1<br>1<br>1<br>4<br>2<br>1<br>1<br>3<br>2<br>1<br>2<br>1<br>2<br>1<br>2<br>2<br>1<br>2<br>1<br>2<br>2<br>~~2~~<br>2<br>1<br>3<br>2<br>1<br>2<br>2<br>2<br>2<br>2<br>4<br>3<br>4<br>1<br>1<br>~~2~~<br>2|
|Pork ‐ rib|4<br>4<br>4<br>4<br>4<br>4<br>4<br>3<br>4<br>3<br>4<br>5<br>5<br>4<br>3<br>4<br>5<br>3<br>4<br>4<br>4<br>4<br>3<br>3<br>2<br>6<br>3<br>4<br>~~5~~<br>3<br>5<br>5<br>2<br>5<br>2<br>4<br>4<br>4<br>4<br>5<br>5<br>3<br>3<br>3<br>~~5~~<br>5|
|Pork ‐ steak|6<br>4<br>6<br>8<br>6<br>6<br>3<br>5<br>5<br>8<br>4<br>3<br>4<br>5<br>3<br>5<br>4<br>7<br>6<br>5<br>3<br>5<br>3<br>2<br>4<br>5<br>3<br>8<br>~~5~~<br>8<br>4<br>2<br>4<br>6<br>1<br>5<br>4<br>5<br>6<br>5<br>4<br>5<br>6<br>5<br>~~4~~<br>5|
|Apple|14<br>12<br>13<br>12<br>10<br>1~~5~~<br>19<br>12<br>5<br>~~1~~4<br>8<br>12<br>6<br>12<br>12<br>13<br>2~~0~~<br>14<br>12<br>11<br>12<br>9<br>9<br>6<br>10<br>15<br>~~4~~<br>5<br>9<br>10<br>4<br>8<br>3<br>8<br>7<br>4<br>10<br>6<br>9<br>6<br>9<br>5<br>1~~1~~<br>8|
|Banana|16<br>14<br>12<br>17<br>12<br>1~~8~~<br>11<br>13<br>13<br>1~~2~~<br>18<br>16<br>19<br>14<br>12<br>19<br>21<br>9<br>15<br>9<br>13<br>11<br>14<br>12<br>12<br>13<br>13<br>17<br>~~12~~<br>16<br>13<br>16<br>17<br>13<br>14<br>10<br>7<br>1~~2~~<br>12<br>10<br>15<br>10<br>16<br>10<br>1~~4~~<br>12|
|Guava|13<br>13<br>10<br>9<br>9<br>1~~2~~<br>9<br>11<br>7<br>9<br>~~1~~2<br>12<br>8<br>9<br>13<br>9<br>12<br>1~~1~~<br>10<br>9<br>13<br>8<br>10<br>13<br>13<br>15<br>13<br>12<br>~~10~~<br>14<br>14<br>14<br>12<br>13<br>9<br>9<br>10<br>8<br>12<br>12<br>10<br>8<br>16<br>9<br>1~~1~~<br>10|
|Lime|22<br>18<br>20<br>22<br>21<br>2~~3~~<br>17<br>18<br>19<br>2~~0~~<br>22<br>22<br>17<br>20<br>19<br>22<br>19<br>1~~9~~<br>21<br>21<br>20<br>18<br>19<br>17<br>18<br>18<br>18<br>19<br>~~20~~<br>24<br>15<br>18<br>19<br>17<br>14<br>21<br>15<br>1~~2~~<br>20<br>20<br>17<br>21<br>29<br>19<br>2~~3~~<br>17|
|Muskmelon|21<br>22<br>18<br>20<br>21<br>2~~0~~<br>14<br>18<br>22<br>2~~4~~<br>19<br>19<br>18<br>22<br>18<br>20<br>18<br>1~~8~~<br>17<br>13<br>15<br>17<br>14<br>15<br>13<br>14<br>14<br>18<br>~~18~~<br>20<br>18<br>15<br>18<br>18<br>18<br>18<br>15<br>1~~6~~<br>16<br>15<br>20<br>20<br>22<br>16<br>1~~5~~<br>17|
|Orange<br>|20<br>14<br>17<br>20<br>20<br>2~~1~~<br>14<br>16<br>20<br>1~~7~~<br>~~2~~1<br>18<br>15<br>14<br>16<br>18<br>21<br>1~~7~~<br>14<br>14<br>16<br>15<br>14<br>12<br>15<br>13<br>17<br>17<br>~~14~~<br>18<br>15<br>16<br>16<br>16<br>14<br>16<br>14<br>1~~5~~<br>16<br>18<br>16<br>13<br>20<br>14<br>1~~8~~<br>15<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>|
|Papaya|13<br>13<br>14<br>16<br>11<br>1~~5~~<br>12<br>13<br>12<br>1~~3~~<br>~~1~~3<br>13<br>11<br>9<br>14<br>13<br>14<br>1~~3~~<br>14<br>13<br>15<br>15<br>13<br>13<br>15<br>14<br>14<br>15<br>~~12~~<br>13<br>12<br>14<br>14<br>14<br>13<br>13<br>13<br>1~~2~~<br>14<br>11<br>13<br>17<br>18<br>11<br>1~~4~~<br>13|
|Pear|12<br>19<br>12<br>15<br>11<br>1~~1~~<br>8<br>13<br>9<br>1~~4~~<br>18<br>12<br>9<br>8<br>12<br>12<br>16<br>1~~1~~<br>12<br>9<br>10<br>9<br>12<br>8<br>12<br>9<br>11<br>10<br>~~10~~<br>13<br>11<br>9<br>8<br>9<br>8<br>6<br>7<br>9<br>13<br>10<br>10<br>15<br>13<br>13<br>1~~3~~<br>10|
|Pineapple|15<br>15<br>18<br>17<br>14<br>1~~1~~<br>13<br>18<br>13<br>1~~8~~<br>14<br>14<br>11<br>8<br>14<br>14<br>15<br>1~~6~~<br>11<br>11<br>13<br>13<br>12<br>11<br>13<br>11<br>13<br>15<br>~~14~~<br>15<br>16<br>16<br>15<br>14<br>16<br>14<br>15<br>1~~5~~<br>10<br>16<br>17<br>19<br>18<br>15<br>1~~4~~<br>12|
|Plantain|6<br>7<br>11<br>2<br>4<br>9<br>6<br>5<br>1~~2~~<br>6<br>6<br>2<br>11<br>3<br>7<br>5<br>7<br>6<br>9<br>9<br>5<br>8<br>7<br>8<br>12<br>8<br>~~8~~<br>8<br>8<br>5<br>8<br>9<br>4<br>9<br>8<br>4<br>9<br>9<br>5<br>10<br>11<br>1~~4~~<br>8|
|Watermelon|24<br>21<br>21<br>23<br>23<br>2~~3~~<br>13<br>23<br>27<br>2~~5~~<br>~~1~~9<br>23<br>19<br>20<br>20<br>20<br>19<br>1~~8~~<br>17<br>15<br>14<br>17<br>16<br>12<br>16<br>11<br>14<br>19<br>~~16~~<br>20<br>15<br>15<br>16<br>15<br>12<br>14<br>12<br>1~~5~~<br>17<br>18<br>15<br>12<br>24<br>12<br>1~~8~~<br>13|
|Avocado|14<br>12<br>15<br>18<br>14<br>1~~6~~<br>14<br>14<br>16<br>1~~7~~<br>16<br>16<br>12<br>12<br>16<br>14<br>14<br>1~~2~~<br>12<br>11<br>13<br>11<br>12<br>10<br>13<br>12<br>11<br>13<br>~~10~~<br>12<br>11<br>12<br>10<br>11<br>10<br>11<br>11<br>1~~1~~<br>14<br>13<br>14<br>11<br>10<br>12<br>1~~5~~<br>10|
|Cabbage|17<br>17<br>27<br>18<br>10<br>1~~4~~<br>5<br>4<br>15<br>2~~0~~<br>10<br>15<br>10<br>37<br>13<br>15<br>17<br>1~~0~~<br>12<br>10<br>16<br>15<br>13<br>11<br>11<br>9<br>10<br>7<br>~~18~~<br>12<br>15<br>13<br>14<br>11<br>5<br>11<br>9<br>1~~5~~<br>13<br>11<br>11<br>22<br>10<br>1~~1~~<br>14|
|Carrot|8<br>11<br>18<br>18<br>12<br>1~~5~~<br>10<br>11<br>13<br>1~~3~~<br>~~1~~5<br>14<br>10<br>10<br>14<br>15<br>14<br>7<br>12<br>12<br>17<br>13<br>12<br>10<br>11<br>12<br>15<br>13<br>~~12~~<br>15<br>8<br>13<br>12<br>11<br>6<br>10<br>9<br>9<br>14<br>12<br>9<br>13<br>10<br>12<br>1~~2~~<br>11|
|Chayote|18<br>21<br>19<br>18<br>9<br>1~~2~~<br>18<br>14<br>20<br>1~~7~~<br>~~1~~8<br>15<br>16<br>16<br>15<br>15<br>18<br>1~~4~~<br>11<br>14<br>20<br>19<br>23<br>17<br>21<br>22<br>20<br>23<br>~~17~~<br>18<br>16<br>21<br>25<br>20<br>9<br>19<br>23<br>1~~7~~<br>17<br>19<br>20<br>17<br>14<br>22<br>2~~2~~<br>17|
|Cucumber|24<br>24<br>24<br>25<br>22<br>2~~4~~<br>21<br>20<br>27<br>2~~6~~<br>~~2~~0<br>23<br>21<br>21<br>28<br>24<br>16<br>2~~5~~<br>19<br>11<br>20<br>23<br>14<br>12<br>20<br>16<br>16<br>23<br>~~18~~<br>21<br>18<br>22<br>26<br>19<br>10<br>17<br>17<br>1~~3~~<br>20<br>18<br>24<br>19<br>19<br>18<br>2~~3~~<br>16|
|Lettuce|23<br>18<br>18<br>23<br>16<br>1~~8~~<br>15<br>12<br>18<br>2~~1~~<br>17<br>15<br>23<br>10<br>23<br>11<br>6<br>9<br>12<br>12<br>14<br>12<br>9<br>13<br>7<br>13<br>13<br>~~10~~<br>14<br>11<br>9<br>11<br>11<br>8<br>9<br>10<br>6<br>13<br>5<br>13<br>9<br>5<br>8<br>1~~3~~<br>10|
|Onion|18<br>18<br>18<br>25<br>19<br>2~~2~~<br>16<br>18<br>18<br>2~~3~~<br>~~2~~0<br>22<br>17<br>20<br>21<br>20<br>20<br>2~~0~~<br>17<br>16<br>18<br>16<br>15<br>16<br>13<br>17<br>17<br>20<br>~~16~~<br>17<br>16<br>17<br>17<br>16<br>14<br>17<br>15<br>1~~6~~<br>18<br>17<br>16<br>17<br>17<br>17<br>1~~7~~<br>16|
|Jalapeno pepper|17<br>21<br>21<br>24<br>16<br>1~~9~~<br>12<br>15<br>18<br>1~~8~~<br>~~2~~1<br>26<br>14<br>20<br>15<br>21<br>20<br>1~~5~~<br>18<br>10<br>15<br>14<br>17<br>8<br>14<br>21<br>14<br>19<br>~~17~~<br>17<br>11<br>15<br>16<br>15<br>12<br>14<br>11<br>1~~6~~<br>20<br>15<br>12<br>14<br>9<br>2~~4~~<br>16|
|Poblano pepper|18<br>17<br>17<br>19<br>16<br>2~~0~~<br>18<br>21<br>17<br>1~~4~~<br>20<br>19<br>14<br>19<br>22<br>19<br>14<br>2~~0~~<br>19<br>15<br>18<br>18<br>17<br>19<br>17<br>15<br>16<br>20<br>~~15~~<br>19<br>16<br>18<br>19<br>19<br>17<br>17<br>15<br>1~~4~~<br>15<br>14<br>18<br>12<br>16<br>12<br>1~~7~~<br>18|
|<br>Serrano pepper|19<br>18<br>15<br>20<br>14<br>2~~0~~<br>17<br>14<br>14<br>1~~7~~<br>17<br>19<br>13<br>15<br>17<br>20<br>19<br>1~~9~~<br>19<br>16<br>17<br>17<br>14<br>17<br>17<br>15<br>17<br>19<br>~~16~~<br>19<br>17<br>16<br>18<br>15<br>15<br>17<br>16<br>1~~4~~<br>16<br>15<br>15<br>16<br>14<br>14<br>1~~3~~<br>16|
|<br>Potato|13<br>14<br>16<br>19<br>16<br>1~~6~~<br>9<br>11<br>18<br>1~~6~~<br>~~1~~5<br>18<br>16<br>17<br>16<br>19<br>19<br>9<br>11<br>11<br>12<br>10<br>12<br>10<br>11<br>14<br>11<br>16<br>~~12~~<br>12<br>10<br>12<br>11<br>11<br>7<br>12<br>9<br>1~~0~~<br>12<br>12<br>10<br>12<br>13<br>11<br>1~~2~~<br>10|
|Tomatillo|20<br>21<br>19<br>20<br>14<br>1~~9~~<br>15<br>14<br>1~~4~~<br>18<br>17<br>11<br>24<br>16<br>20<br>15<br>1~~8~~<br>20<br>17<br>16<br>19<br>19<br>22<br>19<br>20<br>19<br>18<br>~~18~~<br>22<br>13<br>20<br>20<br>20<br>17<br>16<br>16<br>1~~2~~<br>18<br>17<br>16<br>19<br>22<br>14<br>1~~8~~<br>19|
|Tomato ‐ beefsteak|24<br>33<br>29<br>35<br>30<br>3~~3~~<br>24<br>28<br>31<br>2~~1~~<br>30<br>34<br>23<br>21<br>27<br>24<br>28<br>2~~8~~<br>27<br>24<br>20<br>22<br>27<br>24<br>23<br>19<br>22<br>31<br>~~22~~<br>28<br>25<br>23<br>26<br>25<br>31<br>19<br>21<br>2~~6~~<br>24<br>24<br>27<br>28<br>19<br>13<br>2~~1~~<br>23|
|<br>Tomato ‐ roma|25<br>26<br>25<br>34<br>30<br>3~~2~~<br>20<br>25<br>30<br>2~~7~~<br>29<br>24<br>22<br>26<br>24<br>33<br>26<br>1~~8~~<br>22<br>17<br>21<br>21<br>21<br>19<br>23<br>23<br>22<br>27<br>~~20~~<br>25<br>18<br>18<br>21<br>22<br>21<br>23<br>19<br>2~~2~~<br>23<br>17<br>22<br>17<br>22<br>22<br>2~~3~~<br>20|
|Zucchini|24<br>23<br>18<br>24<br>22<br>2~~2~~<br>19<br>19<br>22<br>2~~2~~<br>~~2~~2<br>23<br>18<br>24<br>23<br>23<br>18<br>2~~0~~<br>22<br>18<br>18<br>18<br>22<br>20<br>23<br>19<br>20<br>22<br>~~18~~<br>21<br>18<br>19<br>20<br>19<br>17<br>20<br>19<br>1~~6~~<br>17<br>15<br>17<br>16<br>21<br>12<br>2~~3~~<br>19|
|Salt|4<br>1<br>0<br>1<br>5<br>1<br>6<br>2<br>1<br>9<br>1<br>1<br>1<br>1<br>2<br>1<br>6<br>1<br>1<br>1<br>4<br>1<br>1<br>1<br>3<br>2<br>~~2~~<br>3<br>2<br>5<br>2<br>1<br>2<br>1<br>5<br>2<br>5<br>3<br>3<br>3<br>13<br>6<br>~~9~~<br>3|
|Sugar ‐ 1kg pack|4<br>4<br>7<br>5<br>8<br>3<br>6<br>5<br>5<br>6<br>5<br>5<br>5<br>5<br>5<br>5<br>2<br>5<br>4<br>4<br>3<br>5<br>5<br>4<br>5<br>5<br>~~3~~<br>3<br>4<br>6<br>3<br>4<br>6<br>6<br>4<br>6<br>5<br>5|
|<br>Sugar ‐ 2kg pack<br>Cki il Mid|7<br>6<br>5<br>8<br>7<br>6<br>5<br>4<br>8<br>5<br>4<br>9<br>2<br>5<br>4<br>1~~0~~<br>6<br>1<br>5<br>4<br>5<br>6<br>5<br>5<br>6<br>6<br>~~5~~<br>4<br>6<br>6<br>4<br>5<br>2<br>5<br>7<br>7<br>6<br>6<br>6<br>5<br>8<br>~~5~~<br>5<br>1<br>1<br>3<br>6<br>3<br>5<br>1<br>3<br>1<br>3<br>2<br>5<br>2<br>1<br>2<br>4<br>2<br>1<br>2<br>4<br>5<br>3<br>1<br>1<br>4<br>2<br>~~2~~<br>1<br>4<br>5<br>1<br>3<br>2<br>2<br>2<br>4<br>4<br>3<br>2<br>4<br>3<br>2<br>~~1~~<br>2|
|oong o ‐ xe<br>Cement ‐ 50kg bag|2<br>1<br>1<br>3<br>2<br>2<br>2<br>3<br>1<br>4<br>2<br>4<br>1<br>1<br>2<br>2<br>2<br>3<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>2<br>3<br>~~2~~<br>2<br>3<br>2<br>2<br>2<br>3<br>3<br>2<br>2<br>2<br>3<br>3<br>2<br>3<br>5<br>~~1~~<br>2|

23
- <u>Table 7. Pass through magnitude in cities</u>

||<br>South<br><br>Northern border<br>Northwest<br>Northeast<br>Center north<br>Center south|
|---|---|
||MXL<br>TIJ<br>LAP<br>ACU<br>JUA<br>MAT<br>TPC<br>CUL<br>HMO<br>HUA<br>TOR<br>MVA<br>CHIH<br>JIM<br>DGO<br>MTY<br>TAM<br>FRE<br>AGS<br>COL<br>LEON<br>CTZ<br>GDL<br>TEP<br>MOR<br>JAC<br>QRO<br>SLP<br>ACA<br>IGU<br>TUL<br>TOL<br>CUE<br>PUE<br>TLAX<br>VER<br>COR<br>SAT<br>CAM<br>TAP<br>OAX<br>TEU<br>CHE<br>VSA<br>MID<br>MX|
|Beans|42<br>58<br>65<br>71<br>40<br>63<br>46<br>12<br>21<br>44<br>30<br>25<br>26<br>2~~0~~<br>26<br>13|
|Rice|0<br>131<br>0<br>1~~3~~<br>0<br>0<br>0<br>0<br>14<br>18<br>~~6~~2<br>0<br>0<br>~~40~~<br>0<br>44<br>11<br>0<br>0<br>8<br>0<br>23<br>0|
|Eggs ‐ per piece|41<br>~~4~~0<br>~~4~~2<br>42<br>38<br>41<br>40<br>5~~5~~<br>44<br>23<br>45<br>36<br>43<br>43<br>~~42~~<br>54<br>46<br>29<br>45<br>48<br>46<br>41|
|Eggs ‐ 12 pack|35<br>0<br>~~5~~3<br>0<br>1~~7~~<br>0<br>0<br>24<br>16<br>13<br>13<br>~~4~~<br>27<br>0<br>15<br>23<br>19<br>28<br>0<br>0<br>0<br>0<br>1~~8~~|
|Eggs ‐ 18 pack|0<br>0<br>0<br>0<br>0<br>0<br>0<br>~~3~~5<br>38<br>0<br>44<br>32<br>39<br>17<br>0<br>0<br>0<br>29|
|Eggs ‐ 30 pack|20<br>22<br>18<br>27<br>18<br>20<br>1~~2~~<br>0<br>40<br>0<br>0<br>0<br>0<br>0<br>~~33~~<br>0<br>27<br>39<br>46<br>28<br>47<br>4~~8~~<br>0|
|Milk||
|Bolillo bread||
|Concha bread||
|Corn tortillas||
|Water ‐ 1lt bottle<br>||
|Water ‐ 1.5lt bottle||
|Soda ‐ 2lt bottle||
|Soda ‐ 600ml bottle||
|Beef ‐ chop|77<br>48<br>61<br>58<br>69<br>5~~5~~<br>~~1~~6<br>79<br>0<br>~~6~~9<br>25<br>45<br>63<br>60 105 5~~7~~<br>~~5~~9<br>64<br>37<br>60<br>97<br>12<br>88<br>57<br>72<br>~~67~~<br>61<br>72 129 70<br>51<br>74<br>25<br>69<br>8~~2~~<br>~~1~~9<br>68<br>79<br>54<br>82<br>7~~3~~<br>70|
|Beef ‐ ground|71 100 49<br>58<br>89<br>9~~9~~<br>55<br>67<br>2~~6~~<br>~~6~~6<br>65<br>49<br>51<br>73<br>71<br>36<br>7~~2~~<br>~~7~~0<br>79<br>32<br>85<br>44<br>42<br>61<br>~~82~~<br>61<br>52<br>65<br>89<br>65<br>63<br>57<br>66<br>58<br>8~~6~~<br>~~6~~1<br>76<br>86<br>70<br>89<br>7~~8~~<br>67|
|Beef ‐ rib<br>|70<br>79<br>68<br>45<br>5~~9~~<br>83<br>5~~9~~<br>~~8~~8<br>53<br>58<br>84<br>78<br>2~~8~~<br>40<br>74<br>61<br>~~38~~<br>75<br>55<br>81<br>48<br>70<br>75<br>9~~3~~<br>~~8~~5<br>89<br>84<br>76<br>95<br>88<br>58<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>|
|Beef ‐ steak|58<br>53<br>61<br>64<br>52<br>8~~3~~<br>~~6~~4<br>64<br>66<br>7~~3~~<br>~~4~~4<br>62<br>59<br>69<br>57<br>56<br>58<br>6~~2~~<br>~~6~~6<br>59<br>59<br>71<br>61<br>53<br>74<br>57<br>67<br>~~57~~<br>63<br>68<br>54<br>56<br>56<br>66<br>60<br>61<br>67<br>5~~7~~<br>~~6~~4<br>71<br>67<br>76<br>71<br>73<br>6~~5~~<br>68|
|Chicken ‐ whole|93 129 53 103 107 8~~3 1~~08<br>100<br>~~1~~51 156 158 42 110 126<br>8~~6 1~~12 138 113 109 136 93<br>96<br>97 128<br>~~95~~<br>49 115<br>80 132 138 98<br>90 112 100 9~~4~~<br>~~9~~6 116 144 97<br>27<br>93 1~~10 1~~03|
|Chicken ‐ breast|111 98<br>405 6~~0~~<br>~~6~~5 178<br>138 116<br>97<br>11~~6 1~~28<br>81 107 117<br>118 140 177 1~~12 ~~110 114<br>67 119 94<br>98 124<br>67<br>~~1~~13<br>112 23<br>87 109 9~~7~~<br>96|
|Chicken ‐ roasted|159 62 107 15 11~~7~~<br>62<br>~~7~~0<br>73<br>57<br>84 101<br>99<br>53 11~~1~~<br>106 108 192 102 77<br>59<br>115<br>~~95~~<br>86 171<br>93<br>80 140 65<br>90<br>91<br>78 11~~2 8~~4 111 80 110<br>25<br>68<br>7~~8~~<br>97|
|Pork ‐ rib|20<br>38<br>43<br>36<br>4~~1~~<br>~~3~~3<br>33<br>0<br>~~4~~0<br>39<br>33<br>36<br>31<br>3~~3~~<br>~~2~~6<br>16<br>40<br>36<br>59<br>32<br>30<br>21<br>~~34~~<br>20<br>40<br>37<br>38<br>21<br>40<br>26<br>28<br>17<br>4~~3~~<br>~~3~~0<br>34<br>33<br>29<br>40<br>3~~8~~<br>29|
|Pork ‐ steak|36<br>28<br>33<br>3~~1~~<br>~~2~~9<br>28<br>34<br>2~~5~~<br>40<br>10<br>25<br>20<br>29<br>23<br>2~~7~~<br>~~2~~1<br>24<br>24<br>36<br>27<br>34<br>47<br>22<br>23<br>~~0~~<br>19<br>14<br>16<br>22<br>17<br>32<br>51<br>22<br>3~~2~~<br>~~2~~0<br>24<br>33<br>18<br>28<br>3~~0~~<br>27|
|Apple|41<br>45<br>71<br>39<br>5~~3~~<br>~~2~~8<br>32<br>~~2~~3<br>56<br>92<br>60<br>54<br>39<br>48<br>0<br>~~3~~7<br>58<br>30<br>40<br>33<br>63<br>45<br>~~48~~<br>56<br>45<br>36<br>58<br>44<br>72<br>52<br>59<br>4~~0~~<br>~~4~~1<br>24<br>48<br>18<br>70<br>52<br>50|
|Banana<br>|90 114 59 171 99 15~~1 1~~55 120 126 4~~9 1~~50 111 155 159 191 133 52 31~~7 1~~19 140 36 109 118<br>0<br>115 65<br>1~~23~~<br>132 156 134 157 130 124<br>0<br>117 13~~9 1~~16<br>47<br>98 101<br>98 174 1~~17 1~~08|
|Guava||
|Lime|34<br>34<br>32<br>35<br>39<br>3~~5~~<br>~~4~~0<br>31<br>32<br>3~~7~~<br>~~3~~8<br>39<br>35<br>33<br>35<br>35<br>36<br>3~~9~~<br>~~3~~7<br>37<br>36<br>35<br>38<br>32<br>34<br>31<br>31<br>~~36~~<br>43<br>38<br>34<br>35<br>38<br>34<br>29<br>47<br>40<br>4~~1~~<br>~~5~~9<br>43<br>39<br>35<br>80<br>39<br>5~~2~~<br>35|
|Muskmelon<br>|52<br>56<br>24<br>42<br>48<br>3~~7~~<br>~~2~~3<br>22<br>37<br>3~~2~~<br>~~5~~0<br>46<br>41<br>76<br>52<br>42<br>29<br>4~~0~~<br>~~3~~4<br>17<br>17<br>26<br>22<br>29<br>20<br>26<br>18<br>~~39~~<br>17<br>13<br>17<br>18<br>22<br>19<br>11<br>22<br>22<br>2~~1~~<br>~~2~~0<br>15<br>18<br>14<br>18<br>19<br>1~~8~~<br>20<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>|
|Orange|42<br>33<br>0<br>0<br>40<br>3~~5~~<br>~~2~~2<br>31<br>31<br>0<br>0<br>36<br>28<br>0<br>30<br>28<br>0<br>0<br>~~2~~7<br>28<br>19<br>0<br>0<br>0<br>0<br>40<br>35<br>~~28~~<br>30<br>29<br>0<br>33<br>0<br>29<br>0<br>35<br>30<br>3~~0~~<br>~~5~~3<br>57<br>32<br>42<br>56<br>30<br>4~~3~~<br>30|
|Papaya|36<br>54<br>31<br>50<br>29<br>5~~3~~<br>~~4~~4<br>43<br>49<br>2~~8~~<br>~~4~~1<br>44<br>35<br>42<br>45<br>44<br>41<br>4~~4~~<br>~~5~~1<br>42<br>46<br>70<br>42<br>53<br>59<br>42<br>60<br>~~47~~<br>58<br>61<br>67<br>63<br>74<br>65<br>63<br>45<br>68<br>5~~2~~<br>~~5~~6<br>22<br>58<br>55<br>38<br>47<br>5~~2~~<br>67|
|Pear|38<br>63<br>19<br>52<br>33<br>0<br>~~2~~7<br>36<br>20<br>3~~0~~<br>~~2~~8<br>40<br>27<br>33<br>21<br>20<br>0<br>1~~5~~<br>~~2~~8<br>33<br>29<br>38<br>37<br>32<br>33<br>36<br>14<br>~~42~~<br>48<br>65<br>36<br>23<br>52<br>40<br>17<br>25<br>23<br>2~~7~~<br>~~4~~6<br>31<br>34<br>65<br>33<br>34<br>4~~5~~<br>50|
|Pineapple|0<br>0<br>0<br>26<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>29<br>0<br>0<br>0<br>20<br>0<br>0<br>0<br>16<br>25<br>16<br>17<br>17<br>0<br>14<br>~~0~~<br>21<br>0<br>28<br>0<br>26<br>30<br>51<br>0<br>27<br>0<br>0<br>29<br>42<br>54<br>52<br>24<br>~~0~~<br>26|
|Plantain|69<br>48<br>0<br>0<br>85<br>3~~7 1~~06 98<br>0<br>~~6~~1<br>0<br>0<br>114 80<br>110 50<br>197 46<br>82<br>59<br>0<br>168 112 95<br>93<br>99 132<br>~~4~~8<br>80 112<br>148 87<br>~~0~~<br>95|
|Watermelon|42<br>52<br>23<br>43<br>44<br>4~~1~~<br>~~1~~2<br>25<br>41<br>2~~7~~<br>~~4~~2<br>38<br>38<br>57<br>33<br>39<br>29<br>3~~0~~<br>~~2~~6<br>18<br>13<br>26<br>21<br>23<br>24<br>20<br>17<br>~~30~~<br>24<br>31<br>22<br>20<br>28<br>25<br>16<br>22<br>22<br>2~~6~~<br>~~1~~9<br>24<br>22<br>15<br>26<br>22<br>2~~1~~<br>21|
|Avocado|96<br>90<br>89 101 74<br>9~~2~~<br>~~8~~6<br>78<br>88<br>7~~3~~<br>~~9~~3 103<br>91<br>95<br>96<br>93<br>93<br>8~~9~~<br>~~9~~3<br>81<br>84<br>95<br>88<br>81<br>98<br>83<br>86<br>~~99~~<br>85<br>86<br>88<br>81<br>80<br>84<br>86<br>93<br>82<br>7~~5~~<br>~~8~~3<br>77<br>80<br>61<br>57<br>75<br>8~~9~~<br>86|
|Cabbage|37<br>27<br>46<br>49<br>3~~5~~<br>~~1~~6<br>42<br>0<br>~~3~~0<br>94<br>28<br>0<br>19<br>31<br>0<br>2~~3~~<br>39<br>19<br>32<br>21<br>0<br>0<br>13<br>30<br>27<br>0<br>41<br>14<br>33<br>26<br>11<br>24<br>20<br>1~~9~~<br>~~1~~3<br>0<br>26<br>39<br>26<br>3~~0~~<br>30|
|Carrot|0<br>52<br>25<br>42<br>28<br>3~~6~~<br>~~3~~3<br>29<br>44<br>0<br>~~4~~2<br>40<br>33<br>31<br>37<br>39<br>36<br>3~~6~~<br>~~4~~0<br>41<br>28<br>42<br>32<br>24<br>37<br>35<br>32<br>~~39~~<br>36<br>37<br>33<br>36<br>37<br>35<br>35<br>38<br>41<br>3~~8~~<br>~~3~~8<br>26<br>34<br>34<br>43<br>43<br>3~~5~~<br>31|
|Chayote|38<br>57<br>50<br>35<br>15<br>3~~3~~<br>~~5~~3<br>43<br>53<br>0<br>~~4~~8<br>41<br>48<br>40<br>46<br>44<br>47<br>4~~2~~<br>~~4~~0<br>40<br>56<br>77<br>65<br>58<br>67<br>62<br>51<br>~~72~~<br>57<br>52<br>59<br>49<br>98<br>72<br>26<br>63<br>87<br>6~~6~~<br>~~5~~1<br>48<br>63<br>47<br>39<br>67<br>7~~0~~<br>60|
|Cucumber|38<br>50<br>36<br>42<br>28<br>3~~7~~<br>0<br>39<br>52<br>3~~0~~<br>~~2~~1<br>40<br>43<br>38<br>32<br>41<br>11<br>1~~7~~<br>~~1~~8<br>0<br>18<br>37<br>9<br>0<br>33<br>19<br>21<br>~~28~~<br>31<br>15<br>29<br>28<br>49<br>29<br>18<br>11<br>18<br>1~~1~~<br>~~1~~9<br>14<br>37<br>26<br>0<br>24<br>1~~6~~<br>30|
|Lettuce|28<br>28<br>9<br>13<br>12<br>1~~5~~<br>~~1~~0<br>11<br>15<br>1~~4~~<br>14<br>13<br>21<br>8<br>17<br>0<br>0<br>0<br>8<br>0<br>8<br>8<br>13<br>0<br>0<br>~~10~~<br>7<br>9<br>7<br>0<br>11<br>5<br>0<br>6<br>0<br>0<br>~~1~~4<br>0<br>10<br>6<br>0<br>0<br>1~~2~~<br>6|
|Onion|36<br>38<br>26<br>35<br>32<br>3~~2~~<br>~~2~~9<br>29<br>32<br>2~~0~~<br>~~2~~9<br>34<br>30<br>25<br>35<br>30<br>40<br>2~~5~~<br>~~2~~6<br>26<br>33<br>30<br>32<br>33<br>25<br>21<br>32<br>~~37~~<br>31<br>35<br>28<br>28<br>28<br>26<br>26<br>30<br>29<br>3~~0~~<br>~~3~~2<br>31<br>30<br>24<br>29<br>29<br>2~~7~~<br>27|
|Jalapeno pepper<br>|50<br>66<br>61 121 58<br>8~~1~~<br>~~3~~8<br>43<br>60<br>5~~6~~<br>~~7~~9<br>99<br>46<br>91<br>78<br>89<br>73<br>6~~7~~<br>~~7~~3<br>32<br>39<br>53<br>58<br>41<br>71<br>35<br>~~74~~<br>72<br>79<br>48<br>59<br>71<br>67<br>58<br>63<br>72<br>6~~5~~<br>~~6~~1<br>48<br>32<br>36<br>22<br>2~~6~~<br>69|
|Poblano pepper|48<br>56<br>38<br>86<br>61<br>9~~2~~<br>~~7~~4<br>69<br>50<br>4~~7~~<br>~~7~~9<br>91<br>59<br>85<br>97<br>86<br>66<br>9~~8~~<br>~~8~~4<br>63<br>57<br>80<br>71<br>67<br>76<br>64<br>57<br>~~91~~<br>69<br>69<br>74<br>75<br>80<br>83<br>71<br>68<br>69<br>6~~3~~<br>~~6~~4<br>51<br>73<br>41<br>52<br>51<br>7~~4~~<br>79|
|Serrano pepper|45<br>56<br>31<br>93<br>45<br>9~~3~~<br>~~6~~0<br>45<br>52<br>4~~6~~<br>~~6~~8<br>81<br>42<br>56<br>68<br>90<br>68<br>7~~9~~<br>~~7~~7<br>46<br>48<br>65<br>45<br>53<br>66<br>59<br>55<br>~~80~~<br>73<br>78<br>43<br>55<br>73<br>48<br>48<br>44<br>42<br>5~~5~~<br>~~5~~1<br>45<br>46<br>48<br>44<br>39<br>4~~1~~<br>62|
|Potato|19<br>14<br>0<br>1~~2~~<br>0<br>0<br>0<br>0<br>1~~5~~|
|Tomatillo|66<br>73<br>43<br>81<br>46<br>7~~7~~<br>47<br>33<br>3~~8~~<br>~~7~~3<br>70<br>44<br>63<br>64<br>80<br>49<br>7~~1~~<br>~~7~~2<br>72<br>30<br>85<br>73<br>66<br>74<br>65<br>78<br>~~69~~<br>78<br>98<br>78<br>93<br>87<br>80<br>68<br>81<br>5~~3~~<br>~~7~~6<br>69<br>55<br>68<br>78<br>55<br>6~~3~~<br>85|
|Tomato ‐ beefsteak|47<br>56<br>48<br>72<br>43<br>6~~6~~<br>~~4~~7<br>53<br>58<br>4~~7~~<br>~~6~~2<br>54<br>44<br>25<br>46<br>48<br>51<br>6~~5~~<br>~~4~~5<br>44<br>25<br>49<br>53<br>37<br>47<br>39<br>22<br>~~53~~<br>49<br>55<br>36<br>34<br>63<br>55<br>62<br>34<br>40<br>6~~2~~<br>~~4~~0<br>32<br>50 101<br>35<br>0<br>3~~0~~<br>45|
|Tomato ‐ roma|42<br>43<br>33<br>39<br>36<br>4~~0~~<br>~~2~~9<br>41<br>52<br>3~~9~~<br>~~4~~7<br>38<br>35<br>42<br>29<br>41<br>28<br>2~~3~~<br>~~3~~1<br>28<br>28<br>33<br>34<br>25<br>36<br>38<br>28<br>~~32~~<br>28<br>27<br>23<br>27<br>30<br>23<br>26<br>35<br>22<br>2~~4~~<br>~~2~~4<br>15<br>28<br>14<br>24<br>25<br>2~~0~~<br>31|
|Zucchini|22<br>29<br>11<br>15<br>0<br>1~~3~~<br>7<br>9<br>23<br>1~~6~~<br>~~1~~1<br>11<br>12<br>19<br>0<br>13<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>~~0~~<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>7<br>0<br>0<br>0<br>0<br>0<br>1~~0~~<br>0|
|Salt||
|Sugar ‐ 1kg pack|103<br>0<br>51<br>40<br>69<br>5~~1~~<br>~~5~~3<br>42<br>53<br>5~~8 1~~07 38<br>71<br>54<br>2~~3~~<br>~~3~~3<br>71<br>48<br>46<br>49<br>44<br>~~48~~<br>55<br>51<br>56<br>31<br>53<br>51|
|Sugar ‐ 2kg pack|141 71<br>6~~0~~<br>~~7~~5<br>0<br>42<br>71<br>0<br>54<br>17<br>2~~3~~<br>~~3~~4<br>43<br>62<br>57<br>0<br>50<br>~~71~~<br>77<br>67 133 82<br>63<br>57<br>80<br>57<br>~~7~~3<br>87<br>76<br>0<br>65<br>6~~1~~<br>62|
|Cooking oil ‐ Mixed<br>|0<br>37<br>37<br>1~~0~~<br>17<br>0<br>74<br>38<br>0<br>30<br>~~8~~<br>31<br>1~~8~~<br>~~1~~6<br>14<br>32|
|Cement ‐ 50kg bag||

24
- <u>Table 8. Pass thro</u> ~~<u>ug</u>~~ <u>h speed of adjustment</u> ~~<u>in</u>~~ <u>cities</u>

||ae . assro~~ug~~spee o ausmen~~n~~ces<br>Northern border<br>Northwest<br>Northeast<br>Center north<br>Center south<br>South<br>|
|---|---|
||MXL<br>TIJ<br>LAP<br>ACU<br>JUA<br>MAT<br>TPC<br>CUL<br>HMO<br>HUA<br>TOR<br>MVA<br>CHIH<br>JIM<br>DGO<br>MTY<br>TAM<br>FRE<br>AGS<br>COL<br>LEON<br>CTZ<br>GDL<br>TEP<br>MOR<br>JAC<br>QRO<br>SLP<br>ACA<br>IGU<br>TUL<br>TOL<br>CUE<br>PUE<br>TLAX<br>VER<br>COR<br>SAT<br>CAM<br>TAP<br>OAX<br>TEU<br>CHE<br>VSA<br>MID<br>MX|
|Beans|9<br>16<br>0<br>11<br>7<br>7<br>13<br>10<br>10<br>18<br>11<br>7<br>9<br>15<br>21<br>7|
|Rice|52<br>74<br>47<br>15<br>~~1~~7<br>60<br>46<br>19<br>36<br>47<br>~~5~~4<br>13<br>30<br>3~~4~~<br>68<br>16<br>11<br>54<br>36<br>54<br>~~3~~8<br>35<br>11|
|Eggs ‐ per piece<br>|8<br>4<br>8<br>3<br>3<br>13<br>0<br>5<br>5<br>22<br>4<br>4<br>8<br>5<br>~~4~~<br>6<br>3<br>0<br>4<br>5<br>0<br>2<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>|
|Eggs ‐ 12 pack|20<br>49<br>9<br>63<br>67<br>~~5~~8<br>35<br>13<br>37<br>45<br>47<br>4~~1~~<br>59<br>0<br>51<br>7<br>49<br>67<br>34<br>~~2~~4<br>54<br>84<br>5|
|Eggs ‐ 18 pack|0<br>48<br>20<br>89<br>~~1~~9<br>33<br>17<br>~~3~~4<br>24<br>60<br>20<br>8<br>15<br>52<br>64<br>99<br>~~2~~7<br>9|
|Eggs ‐ 30 pack<br>|15<br>17<br>26<br>5<br>15<br>11<br>9<br>~~2~~0<br>11<br>72<br>79<br>28<br>34<br>61<br>1~~2~~<br>30<br>21<br>5<br>5<br>7<br>0<br>2~~2~~<br>75|
|Milk||
|Bolillo bread<br>Concha bread||
|<br>Corn tortillas||
|Water ‐ 1lt bottle<br>Water ‐ 1.5lt bottle||
|Soda ‐ 2lt bottle||
|Soda ‐ 600ml bottle||
|Beef ‐ chop|21<br>26<br>23<br>21<br>3<br>45<br>~~0~~<br>5<br>72<br>~~1~~8<br>19<br>6<br>0<br>6<br>65<br>7<br>~~4~~<br>0<br>0<br>11<br>6<br>4<br>3<br>8<br>14<br>1~~2~~<br>6<br>8<br>8<br>6<br>0<br>7<br>0<br>6<br>37<br>~~3~~6<br>25<br>15<br>30<br>0<br>1~~1~~<br>4|
|Beef ‐ ground|0<br>4<br>0<br>13<br>17<br>2<br>8<br>5<br>11<br>~~1~~0<br>9<br>7<br>12<br>7<br>8<br>17<br>8<br>~~1~~7<br>0<br>8<br>6<br>0<br>9<br>4<br>~~6~~<br>8<br>15<br>9<br>4<br>9<br>8<br>6<br>7<br>3<br>6<br>7<br>4<br>5<br>8<br>6<br>1~~1~~<br>2|
|Beef ‐ rib|11<br>10<br>10<br>30<br>13<br>16<br>36<br>~~1~~7<br>31<br>0<br>23<br>5<br>7<br>8<br>9<br>24<br>3~~3~~<br>4<br>13<br>4<br>6<br>22<br>11<br>35<br>5<br>23<br>7<br>0<br>0<br>7<br>4|
|Beef ‐ steak|5<br>5<br>5<br>9<br>5<br>6<br>4<br>7<br>7<br>9<br>~~1~~8<br>4<br>11<br>2<br>12<br>6<br>6<br>7<br>~~3~~<br>4<br>0<br>6<br>0<br>0<br>4<br>3<br>4<br>~~5~~<br>6<br>9<br>2<br>6<br>3<br>3<br>5<br>0<br>4<br>4<br>4<br>7<br>7<br>0<br>4<br>3<br>4<br>2|
|Chicken ‐ whole|38<br>30<br>35<br>43<br>16<br>33<br>~~2~~4<br>30<br>~~1~~6<br>0<br>17<br>23<br>51<br>19<br>26<br>~~2~~1<br>17<br>15<br>36<br>15<br>16<br>43<br>24<br>27<br>2~~4~~<br>46<br>63<br>27<br>47<br>26<br>18<br>32<br>23<br>23<br>41<br>~~3~~8<br>67<br>52<br>48<br>27<br>24<br>5~~8~~<br>16|
|Chicken ‐ breast<br>|43<br>74<br>28<br>23<br>9<br>14<br>6<br>33<br>24<br>48<br>~~4~~7<br>28<br>21<br>33<br>27<br>36<br>12<br>6~~5~~<br>83<br>30<br>61<br>21<br>53<br>60<br>22<br>26<br>~~7~~5<br>37<br>31<br>73<br>16<br>4~~3~~<br>48<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>|
|Chicken ‐ roasted|12<br>23<br>10<br>26<br>2<br>5<br>~~3~~3<br>17<br>23<br>17<br>18<br>19<br>35<br>31<br>12<br>10<br>14<br>12<br>8<br>11<br>13<br>2~~3~~<br>19<br>18<br>26<br>19<br>17<br>22<br>49<br>28<br>7<br>18<br>~~2~~4<br>32<br>69<br>18<br>40<br>68<br>3~~1~~<br>0|
|Pork ‐ rib|15<br>9<br>0<br>11<br>8<br>~~1~~4<br>6<br>69<br>9<br>9<br>7<br>7<br>18<br>7<br>~~8~~<br>8<br>8<br>7<br>0<br>8<br>20<br>4<br>2~~1~~<br>10<br>5<br>11<br>7<br>7<br>7<br>11<br>7<br>9<br>21<br>5<br>6<br>8<br>9<br>5<br>1~~0~~<br>6|
|Pork ‐ steak|12<br>12<br>15<br>10<br>~~7~~<br>9<br>13<br>51<br>7<br>11<br>22<br>10<br>8<br>18<br>22<br>~~1~~8<br>14<br>7<br>12<br>5<br>0<br>5<br>20<br>8<br>3~~8~~<br>12<br>34<br>23<br>5<br>9<br>13<br>0<br>14<br>19<br>~~1~~5<br>23<br>7<br>19<br>10<br>9<br>6|
|Apple|57<br>48<br>18<br>43<br>59<br>~~2~~3<br>27<br>~~1~~8<br>19<br>15<br>39<br>38<br>34<br>21 14~~6~~<br>~~6~~7<br>54<br>29<br>53<br>40<br>17<br>39<br>4~~1~~<br>59<br>34<br>9<br>45<br>18<br>6<br>20<br>13<br>16<br>~~1~~8<br>28<br>23<br>33<br>54<br>19<br>0|
|Banana<br>G|19<br>16<br>15<br>19<br>15<br>29<br>~~1~~6<br>15<br>14<br>37<br>~~2~~2<br>19<br>21<br>13<br>13<br>10<br>31<br>26<br>~~1~~2<br>35<br>26<br>15<br>15<br>20<br>26<br>40<br>1~~7~~<br>49<br>13<br>15<br>16<br>9<br>20<br>41<br>19<br>26<br>~~1~~7<br>46<br>30<br>20<br>46<br>10<br>1~~3~~<br>9|
|uava<br>Lime|0<br>0<br>0<br>0<br>0<br>0<br>~~0~~<br>0<br>0<br>10<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>~~0~~<br>0<br>0<br>0<br>0<br>9<br>0<br>0<br>0<br>~~0~~<br>0<br>21<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>~~1~~7<br>19<br>0<br>19<br>17<br>0<br>1~~5~~<br>0|
|Muskmelon|29<br>40<br>43<br>24<br>29<br>25<br>~~2~~2<br>23<br>33<br>62<br>~~1~~5<br>16<br>22<br>20<br>13<br>21<br>18<br>25<br>~~2~~6<br>22<br>34<br>26<br>19<br>46<br>17<br>25<br>20<br>2~~1~~<br>28<br>41<br>33<br>17<br>28<br>24<br>37<br>25<br>25<br>47<br>~~2~~4<br>24<br>29<br>88<br>48<br>23<br>2~~3~~<br>20|
|Orange|19<br>18<br>20<br>13<br>13<br>9<br>9<br>13<br>13<br>20<br>9<br>9<br>8<br>10<br>9<br>6<br>13<br>10<br>~~6~~<br>8<br>11<br>10<br>9<br>11<br>8<br>8<br>9<br>~~8~~<br>8<br>11<br>6<br>9<br>7<br>8<br>8<br>13<br>7<br>9<br>7<br>10<br>9<br>14<br>15<br>9<br>9<br>0|
|Papaya|17<br>10<br>28<br>23<br>20<br>17<br>~~2~~3<br>21<br>19<br>26<br>~~1~~4<br>16<br>18<br>22<br>26<br>14<br>17<br>33<br>~~2~~2<br>27<br>26<br>19<br>17<br>32<br>22<br>24<br>18<br>1~~9~~<br>17<br>22<br>13<br>15<br>15<br>14<br>17<br>16<br>12<br>20<br>~~1~~7<br>22<br>18<br>43<br>33<br>15<br>1~~8~~<br>11|
|Pear|29<br>34<br>19<br>37<br>40<br>68<br>~~1~~6<br>20<br>30<br>31<br>~~2~~9<br>23<br>29<br>27<br>17<br>10<br>23<br>34<br>~~2~~3<br>17<br>25<br>18<br>17<br>29<br>21<br>13<br>22<br>1~~6~~<br>16<br>24<br>19<br>19<br>22<br>16<br>44<br>42<br>11<br>29<br>~~1~~9<br>39<br>20<br>36<br>35<br>42<br>2~~0~~<br>12|
|Pineapple|13<br>16<br>40<br>19<br>10<br>8<br>~~2~~0<br>19<br>14<br>41<br>~~1~~1<br>21<br>10<br>14<br>10<br>10<br>26<br>28<br>~~1~~4<br>11<br>13<br>10<br>17<br>17<br>14<br>14<br>1~~8~~<br>11<br>31<br>17<br>11<br>13<br>10<br>36<br>15<br>12<br>14<br>7<br>18<br>22<br>29<br>25<br>12<br>3~~0~~<br>6|
|Plantain|28<br>52<br>41<br>0<br>22<br>38<br>8<br>33<br>52<br>~~5~~9<br>10<br>~~1~~6<br>7<br>7<br>0<br>22<br>7<br>33<br>19<br>53<br>31<br>0<br>12<br>10<br>16<br>22<br>8<br>~~1~~4<br>18<br>13<br>31<br>28<br>4~~6~~<br>4|
|Watermelon|30<br>26<br>30<br>22<br>32<br>18<br>~~4~~1<br>30<br>33<br>47<br>~~1~~7<br>21<br>23<br>25<br>21<br>17<br>15<br>29<br>~~2~~6<br>21<br>35<br>26<br>21<br>29<br>16<br>29<br>26<br>2~~4~~<br>20<br>31<br>31<br>20<br>25<br>20<br>41<br>16<br>18<br>24<br>~~1~~6<br>30<br>19<br>27<br>28<br>17<br>1~~9~~<br>13|
|Avocado|18<br>13<br>22<br>16<br>19<br>14<br>~~1~~0<br>16<br>15<br>32<br>~~1~~5<br>17<br>11<br>11<br>15<br>11<br>19<br>24<br>~~1~~1<br>12<br>19<br>13<br>9<br>17<br>13<br>16<br>10<br>~~9~~<br>12<br>17<br>13<br>17<br>10<br>9<br>13<br>11<br>9<br>18<br>~~1~~6<br>20<br>12<br>21<br>24<br>13<br>1~~9~~<br>8|
|Cabbage|26<br>54<br>43<br>22<br>24<br>~~1~~9<br>20<br>35<br>~~1~~7<br>15<br>14 105 33<br>24<br>21<br>25<br>22<br>27<br>30<br>10<br>20<br>23<br>27<br>20<br>28<br>23<br>29<br>29<br>19<br>12<br>42<br>19<br>27<br>43<br>~~1~~6<br>43<br>33<br>34<br>11<br>1~~3~~<br>31|
|Carrot|65<br>26<br>39<br>30<br>34<br>18<br>~~1~~7<br>15<br>13<br>35<br>~~2~~1<br>13<br>15<br>28<br>18<br>16<br>13<br>20<br>~~1~~8<br>15<br>20<br>13<br>17<br>20<br>13<br>21<br>16<br>~~9~~<br>8<br>12<br>7<br>10<br>7<br>7<br>8<br>0<br>0<br>10<br>8<br>15<br>0<br>15<br>6<br>8<br>9<br>0|
|Chayote|26<br>28<br>20<br>25<br>18<br>11<br>~~2~~2<br>17<br>32<br>29<br>~~2~~4<br>15<br>20<br>43<br>15<br>12<br>22<br>19<br>~~2~~2<br>18<br>32<br>16<br>18<br>30<br>22<br>29<br>33<br>1~~9~~<br>22<br>34<br>28<br>34<br>28<br>22<br>34<br>24<br>29<br>26<br>~~2~~4<br>25<br>23<br>39<br>41<br>24<br>1~~9~~<br>17|
|Cucumber|37<br>30<br>34<br>32<br>23<br>24<br>~~3~~2<br>43<br>43<br>45<br>~~2~~2<br>24<br>24<br>32<br>31<br>24<br>26<br>30<br>~~1~~6<br>14<br>36<br>31<br>18<br>20<br>22<br>29<br>26<br>2~~4~~<br>28<br>32<br>37<br>43<br>37<br>24<br>19<br>24<br>29<br>29<br>~~2~~2<br>29<br>35<br>40<br>42<br>23<br>2~~3~~<br>23|
|Lettuce|42<br>42<br>34<br>52<br>37<br>26<br>~~3~~2<br>20<br>16<br>29<br>25<br>24<br>53<br>26<br>31<br>36<br>31<br>~~2~~6<br>27<br>19<br>16<br>21<br>46<br>15<br>29<br>3~~7~~<br>19<br>31<br>32<br>29<br>27<br>25<br>36<br>27<br>19<br>26<br>~~2~~1<br>19<br>19<br>31<br>26<br>32<br>1~~9~~<br>18|
|Onion|6<br>0<br>7<br>7<br>6<br>8<br>~~1~~0<br>10<br>6<br>14<br>5<br>7<br>6<br>9<br>7<br>6<br>7<br>8<br>8<br>8<br>10<br>7<br>0<br>13<br>8<br>11<br>12<br>~~7~~<br>6<br>13<br>8<br>6<br>7<br>7<br>8<br>7<br>8<br>8<br>7<br>8<br>7<br>11<br>8<br>8<br>1~~0~~<br>6|
|Jalapeno pepper|51<br>47<br>56<br>65<br>30<br>56<br>~~4~~0<br>33<br>47<br>34<br>~~4~~7<br>71<br>38<br>41<br>47<br>54<br>59<br>58<br>~~5~~0<br>44<br>41<br>20<br>49<br>63<br>66<br>35<br>5~~1~~<br>41<br>65<br>33<br>32<br>51<br>35<br>45<br>36<br>29<br>57<br>~~4~~5<br>46<br>58<br>40<br>23<br>7~~6~~<br>25|
|Poblano pepper|22<br>17<br>9<br>28<br>22<br>19<br>~~1~~8<br>13<br>28<br>14<br>~~3~~1<br>19<br>29<br>25<br>17<br>14<br>13<br>26<br>~~1~~6<br>17<br>32<br>33<br>11<br>51<br>17<br>27<br>11<br>1~~4~~<br>13<br>32<br>20<br>22<br>10<br>12<br>17<br>30<br>25<br>19<br>~~1~~8<br>19<br>26<br>23<br>29<br>20<br>2~~1~~<br>0|
|Serrano pepper|28<br>36<br>22<br>39<br>28<br>53<br>~~3~~2<br>29<br>48<br>39<br>~~3~~9<br>35<br>35<br>40<br>32<br>49<br>32<br>49<br>~~4~~2<br>25<br>30<br>32<br>25<br>51<br>38<br>29<br>34<br>3~~8~~<br>24<br>34<br>18<br>24<br>32<br>58<br>41<br>25<br>28<br>30<br>~~2~~1<br>18<br>30<br>47<br>27<br>25<br>1~~7~~<br>26|
|Potato|20<br>15<br>21<br>14<br>14<br>11<br>20<br>13<br>1~~0~~|
|Tomatillo|26<br>35<br>42<br>38<br>29<br>41<br>40<br>34<br>34<br>~~4~~5<br>33<br>24<br>78<br>33<br>18<br>24<br>23<br>~~1~~7<br>35<br>27<br>23<br>36<br>37<br>33<br>48<br>31<br>2~~9~~<br>30<br>24<br>37<br>0<br>19<br>0<br>26<br>15<br>27<br>~~3~~8<br>30<br>33<br>33<br>31<br>29<br>3~~3~~<br>0|
|Tomato ‐ beefsteak|32<br>60<br>32<br>41<br>40<br>36<br>~~3~~4<br>34<br>36<br>32<br>~~3~~2<br>25<br>31<br>34<br>30<br>26<br>26<br>50<br>~~3~~0<br>28<br>40<br>31<br>41<br>36<br>47<br>34<br>37<br>3~~8~~<br>40<br>49<br>31<br>38<br>48<br>32<br>45<br>30<br>27<br>37<br>~~3~~1<br>37<br>35<br>56<br>36<br>45<br>4~~1~~<br>33|
|Tomato ‐ roma<br>|28<br>26<br>23<br>34<br>33<br>27<br>~~2~~1<br>21<br>27<br>35<br>~~2~~7<br>22<br>25<br>34<br>23<br>25<br>24<br>20<br>~~2~~1<br>23<br>28<br>27<br>20<br>28<br>21<br>34<br>29<br>2~~4~~<br>23<br>23<br>22<br>23<br>21<br>20<br>23<br>21<br>17<br>21<br>~~3~~1<br>20<br>22<br>22<br>28<br>21<br>2~~8~~<br>21|
|Zucchini|37<br>30<br>37<br>27<br>13<br>21<br>~~3~~6<br>38<br>37<br>47<br>~~1~~8<br>21<br>16<br>25<br>22<br>18<br>19<br>20<br>~~2~~3<br>33<br>22<br>21<br>30<br>35<br>28<br>29<br>28<br>2~~0~~<br>24<br>30<br>22<br>25<br>28<br>25<br>29<br>21<br>26<br>25<br>~~3~~7<br>21<br>37<br>39<br>52<br>24<br>2~~7~~<br>24|
|Salt||
|Sugar ‐ 1kg pack|18<br>66<br>12<br>10<br>8<br>5<br>~~7~~<br>12<br>0<br>9<br>~~1~~6<br>6<br>8<br>4<br>24<br>~~3~~3<br>0<br>17<br>0<br>6<br>10<br>2~~7~~<br>5<br>0<br>12<br>11<br>20<br>3|
|Sugar ‐ 2kg pack|31<br>12<br>5<br>9<br>31<br>9<br>21<br>0<br>5<br>27<br>29<br>~~2~~1<br>5<br>5<br>4<br>23<br>6<br>~~6~~<br>6<br>6<br>6<br>3<br>5<br>6<br>3<br>11<br>5<br>5<br>3<br>42<br>9<br>3<br>2|
|<br>Cooking oil ‐ Mixed|13<br>24<br>14<br>13<br>22<br>29<br>0<br>51<br>38<br>16<br>1~~9~~<br>33<br>10 ~~11~~4<br>19<br>38|
|Cement ‐ 50kg bag||

25
- <u>Table 9. Pass through magnitude asymmetry in cities</u>

||<br>South<br><br>Northern border<br>Northwest<br>Northeast<br>Center north<br>Center south|
|---|---|
||MXL<br>TIJ<br>LAP<br>ACU<br>JUA<br>MAT<br>TPC<br>CUL<br>HMO<br>HUA<br>TOR<br>MVA<br>CHIH<br>JIM<br>DGO<br>MTY<br>TAM<br>FRE<br>AGS<br>COL<br>LEON<br>CTZ<br>GDL<br>TEP<br>MOR<br>JAC<br>QRO<br>SLP<br>ACA<br>IGU<br>TUL<br>TOL<br>CUE<br>PUE<br>TLAX<br>VER<br>COR<br>SAT<br>CAM<br>TAP<br>OAX<br>TEU<br>CHE<br>VSA<br>MID<br>MX|
|Beans|0<br>0<br>0<br>‐19<br>0<br>0<br>0<br>0<br>0<br>0<br>‐20<br>0<br>0<br>0<br>0<br>0|
|Rice|0<br>0<br>0<br>22<br>~~2~~4<br>80<br>‐31 ‐2~~3~~<br>0<br>49<br>~~‐6~~5<br>0<br>0<br>~~0~~<br>0<br>0<br>0<br>61<br>0<br>0<br>~~‐3~~4<br>0<br>21|
|Eggs ‐ per piece<br>Eggs ‐ 12 pack|0<br>~~1~~5<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>20<br>22<br>0<br>16<br>~~0~~<br>0<br>14<br>0<br>0<br>19<br>0<br>20<br>0<br>0<br>0<br>0<br>24~~6~~<br>~~#~~#<br>81<br>‐46<br>0<br>0<br>0<br>‐~~70~~<br>##<br>0<br>‐60<br>0<br>0<br>0<br>0<br>0<br>##<br>0<br>0|
|<br>Eggs ‐ 18 pack|##<br>0<br>0<br>117<br>0<br>0<br>0<br>~~0~~<br>‐99<br>0<br>‐41 ‐27 ‐50<br>0<br>##<br>0<br>0<br>0|
|Eggs ‐ 30 pack|0<br>0<br>‐64<br>0<br>‐33<br>0<br>0<br>~~‐7~~1<br>0<br>122<br>0<br>0<br>0<br>0<br>‐~~42~~<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>92|
|Milk||
|Bolillo bread||
|Concha bread||
|Corn tortillas||
|Water ‐ 1lt bottle||
|Water ‐ 1.5lt bottle||
|Soda ‐ 2lt bottle||
|Soda ‐ 600ml bottle||
|Beef ‐ chop|62<br>0<br>‐44<br>0<br>0<br>‐4~~8~~<br>~~0~~<br>0<br>0<br>0<br>‐33<br>0<br>0<br>0<br>0<br>0<br>~~‐1~~4<br>‐7<br>0<br>‐37<br>0<br>0<br>0<br>0<br>‐31<br>~~0~~<br>0<br>0<br>‐19<br>0<br>‐10<br>0<br>0<br>0<br>0<br>~~‐3~~3 ‐86<br>0<br>0<br>0<br>0<br>~~‐~~13|
|Beef ‐ ground|0<br>0<br>0<br>0<br>0<br>‐1~~4~~<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>‐1~~9 ‐3~~5<br>0<br>0<br>0<br>0<br>0<br>‐14<br>~~0~~<br>16<br>‐20 ‐13 ‐17<br>0<br>0<br>0<br>12<br>0<br>0<br>~~‐1~~8<br>0<br>0<br>0<br>‐24<br>0<br>‐6|
|Beef ‐ rib|0<br>‐32<br>0<br>0<br>0<br>0<br>30<br>~~‐4~~1<br>0<br>0<br>0<br>‐12<br>0<br>0<br>‐49<br>0<br>~~0~~<br>0<br>0<br>0<br>‐6<br>0<br>‐20 ‐4~~5 ‐1~~3 ‐91 ‐29<br>0<br>0<br>0<br>0|
|Beef ‐ steak|0<br>0<br>0<br>‐30<br>14<br>‐2~~3~~<br>~~0~~<br>0<br>‐13<br>0<br>~~2~~3<br>0<br>‐20<br>0<br>0<br>0<br>0<br>0<br>~~‐1~~0<br>0<br>0<br>0<br>0<br>0<br>0<br>12<br>0<br>~~0~~<br>0<br>0<br>0<br>0<br>0<br>‐7<br>‐11<br>0<br>‐10<br>0<br>0<br>‐25‐16<br>9<br>9<br>‐19‐1~~2~~<br>‐5|
|<br>Chicken ‐ whole|<br><br><br> <br><br>‐57<br>0<br>‐34 ‐57 ‐29 ‐4~~7~~<br>~~0~~<br>0<br>0<br>0<br>‐39<br>0<br>0<br>0<br>0<br>~~0~~<br>0<br>0<br>0<br>29<br>0<br>0<br>0<br>‐78 ‐~~33~~<br>0<br>‐59<br>0<br>0<br>0<br>0<br>0<br>0<br>‐47<br>0<br>0<br>‐43<br>0<br>0<br>0<br>0<br>0<br>0|
|Chicken ‐ breast|0<br>0<br>0<br>‐2~~2~~<br>~~0~~<br>0<br>0<br>‐58<br>26<br>0<br>~~0~~<br>0<br>0<br>‐36<br>‐54<br>0<br>0<br>~~0~~<br>0<br>‐67<br>‐89<br>0<br>‐49 ‐56<br>0<br>0<br>0<br>0<br>0<br>‐49<br>0<br>0<br>~~‐~~41|
|Chicken ‐ roasted|0<br>‐66<br>29<br>0<br>0<br>0<br>~~‐4~~5<br>0<br>34<br>0<br>0<br>0<br>‐83 ‐5~~9~~<br>0<br>‐30<br>0<br>0<br>0<br>0<br>0<br>~~0~~<br>0<br>0<br>36<br>0<br>‐26<br>0<br>‐70<br>61<br>15<br>0<br>0<br>‐76<br>0<br>0<br>‐93 117 ‐6~~1~~<br>0|
|Pork ‐ rib|0<br>0<br>13<br>0<br>0<br>~~0~~<br>0<br>0<br>0<br>0<br>11<br>0<br>0<br>0<br>~~0~~<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>~~0~~<br>0<br>‐16 ‐29<br>0<br>‐12<br>0<br>0<br>0<br>0<br>‐3~~1~~<br>~~‐~~9<br>0<br>‐18 ‐25<br>0<br>0<br>0|
|Pork ‐ steak|‐15<br>0<br>0<br>14<br>~~0~~<br>0<br>0<br>‐5~~5~~<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>~~‐4~~3<br>0<br>‐21<br>0<br>‐11<br>17<br>0<br>‐44 ‐19 ‐~~47 ~~‐14 ‐74<br>0<br>0<br>‐25<br>0<br>0<br>22<br>‐4~~0 ‐2~~3<br>0<br>0<br>0<br>‐15 ‐1~~9~~<br>0|
|Apple|0<br>‐35<br>0<br>36<br>‐6~~7~~<br>~~0~~<br>0<br>0<br>0<br>‐28 ‐66<br>0<br>0<br>0<br>0<br>~~0~~<br>0<br>0<br>‐85<br>0<br>0<br>0<br>‐~~28~~<br>0<br>‐47<br>0<br>‐51<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>47<br>0<br>24<br>0|
|Banana|0<br>0<br>0<br>0<br>0<br>0<br>~~‐2~~5<br>0<br>0<br>0<br>~~‐3~~2<br>0<br>0<br>0<br>‐42<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>43<br>33<br>~~0~~<br>‐28<br>0<br>0<br>0<br>0<br>0<br>0<br>‐52<br>0<br>0<br>‐59<br>0<br>‐21<br>0<br>0<br>0<br>0|
|Guava||
|Lime|0<br>0<br>0<br>0<br>0<br>0<br>~~0~~<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>‐3~~1~~<br>~~0~~<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>~~0~~<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>‐30<br>0<br>0<br>0<br>38<br>0<br>0<br>0<br>0<br>0<br>0|
|Muskmelon|0<br>0<br>0<br>‐27<br>34<br>0<br>0<br>0<br>0<br>‐6~~4~~<br>0<br>0<br>0<br>0<br>0<br>0<br>‐32<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>‐38<br>0<br>~~0~~<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>‐34<br>0<br>0<br>0<br>0<br>‐36<br>##<br>‐38<br>0<br>0<br>0|
|Orange|0<br>0<br>0<br>0<br>0<br>0<br>~~0~~<br>0<br>0<br>0<br>0<br>0<br>14<br>0<br>0<br>17<br>0<br>0<br>~~0~~<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>~~0~~<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>17|
|Papaya|0<br>0<br>0<br>41<br>0<br>34<br>~~2~~3<br>28<br>0<br>0<br>0<br>45<br>42<br>37<br>32<br>19<br>0<br>32<br>~~2~~3<br>35<br>0<br>0<br>34<br>0<br>27<br>28<br>35<br>2~~8~~<br>33<br>23<br>22<br>36<br>0<br>0<br>0<br>0<br>0<br>0<br>~~1~~9<br>0<br>0<br>0<br>0<br>24<br>0<br>23|
|Pear|0<br>26<br>0<br>‐50<br>0<br>‐9~~8~~<br>~~3~~7<br>17<br>49<br>0<br>0<br>0<br>0<br>28<br>0<br>15<br>0<br>0<br>~~0~~<br>0<br>0<br>0<br>22<br>0<br>0<br>0<br>27<br>~~0~~<br>0<br>0<br>0<br>21<br>30<br>22<br>‐38<br>0<br>0<br>‐2~~7~~<br>0<br>0<br>0<br>46<br>0<br>‐48<br>0<br>23|
|Pineapple|0<br>0<br>‐52<br>0<br>0<br>0<br>~~0~~<br>0<br>0<br>‐5~~1~~<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>‐17<br>0<br>‐18<br>~~0~~<br>0<br>‐27 ‐36<br>0<br>0<br>0<br>‐74<br>0<br>0<br>0<br>~~1~~5<br>0<br>0<br>‐31<br>0<br>0<br>0<br>0|
|Plantain|0<br>‐76<br>0<br>‐38<br>0<br>0<br>~~0~~<br>0<br>‐9~~8~~<br>~~6~~7<br>‐26<br>~~‐3~~4<br>0<br>0<br>0<br>‐26<br>0<br>0<br>0<br>‐84<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>33<br>0<br>0<br>‐5~~6~~<br>15|
|Watermelon|0<br>0<br>0<br>‐40<br>0<br>0<br>~~‐2~~9 ‐38 ‐33<br>0<br>~~‐2~~9<br>0<br>0<br>0<br>0<br>0<br>‐30<br>0<br>~~0~~<br>‐29<br>0<br>0<br>0<br>0<br>‐30<br>0<br>0<br>~~0~~<br>‐29 ‐39 ‐31<br>0<br>‐28<br>0<br>‐44<br>0<br>0<br>‐4~~7 ‐2~~5 ‐63<br>0<br>0<br>‐49<br>0<br>0<br>0|
|Ad|29<br>24<br>0<br>0<br>0<br>0<br>~~0~~<br>0<br>0<br>3~~7~~<br>0<br>0<br>0<br>22<br>0<br>0<br>0<br>61<br>~~0~~<br>0<br>0<br>36<br>0<br>0<br>22<br>0<br>0<br>2~~9~~<br>0<br>23<br>24<br>0<br>0<br>0<br>0<br>0<br>0<br>21<br>0<br>0<br>0<br>0<br>0<br>0<br>3~~9~~<br>0|
|vocao<br>Cabbage|‐<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>0<br>0<br>‐42<br>0<br>‐2~~0~~<br>~~0~~<br>0<br>‐3~~8~~<br>0<br>0<br>0<br>##<br>‐34<br>0<br>0<br>0<br>32<br>23<br>‐27<br>0<br>0<br>0<br>0<br>‐43<br>‐53<br>0<br>‐33<br>0<br>‐19<br>0<br>0<br>‐52 ‐33<br>0<br>0<br>0<br>‐35<br>0<br>0<br>0<br>0|
|Carrot|133<br>0<br>0<br>0<br>0<br>0<br>~~0~~<br>0<br>0<br>0<br>~~‐3~~7<br>0<br>0<br>0<br>33<br>43<br>22<br>0<br>~~3~~6<br>19<br>0<br>0<br>40<br>0<br>0<br>0<br>0<br>~~0~~<br>0<br>0<br>0<br>0<br>0<br>20<br>22<br>14<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>17|
|Chayote|0<br>0<br>0<br>0<br>41<br>0<br>~~3~~1<br>0<br>0<br>0<br>0<br>0<br>29<br>0<br>41<br>22<br>43<br>0<br>~~0~~<br>32<br>0<br>31<br>31<br>31<br>21<br>0<br>0<br>~~0~~<br>38<br>0<br>57<br>0<br>0<br>23<br>0<br>0<br>0<br>0<br>0<br>0<br>47<br>0<br>33<br>37<br>0<br>24|
|Cucumber|0<br>31<br>0<br>0<br>0<br>29<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>45<br>32<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>43<br>42<br>27<br>27<br>37<br>3~~5~~<br>0<br>0<br>50<br>45<br>49<br>0<br>35<br>0<br>0<br>‐2~~5~~<br>~~2~~3<br>37<br>39<br>0<br>0<br>0<br>0<br>38|
|Lettuce|0<br>0<br>‐52<br>0<br>0<br>0<br>~~0~~<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>29<br>0<br>0<br>~~0~~<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>‐~~29~~<br>0<br>31<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>~~2~~9<br>0<br>0<br>0<br>‐50<br>0<br>‐2~~6~~<br>0|
|Onion|0<br>0<br>0<br>0<br>‐17<br>0<br>~~0~~<br>0<br>‐16 ‐1~~9~~<br>0<br>‐15<br>0<br>0<br>0<br>0<br>‐16<br>0<br>~~0~~<br>0<br>‐23 ‐15 ‐13<br>0<br>‐22<br>0<br>‐24<br>~~0~~<br>0<br>‐28<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>~~‐1~~4<br>0<br>0<br>0<br>0<br>0<br>‐1~~6~~<br>0|
|Jl|0<br>0<br>0<br><br>26<br>0<br>~~0~~<br>43<br>0<br>0<br>~~3~~6<br>0<br>0<br>0<br>0<br>2<br>0<br>~~0~~<br>~~0~~<br>0<br>0<br>41<br>0<br>0<br>0<br>0<br>3~~2~~<br>0<br>0<br>0<br>0<br>39<br>0<br>0<br>0<br>0<br>0<br>0<br>39<br>0<br>0<br>0<br>0<br>0|
|aapeno pepper|‐55<br><br><br><br>‐<br><br><br><br><br><br><br><br>5<br><br>‐5<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>|
|Poblano pepper|0<br>0<br>0<br>0<br>29<br>0<br>0<br>0<br>27<br>0<br>0<br>0<br>0<br>‐43<br>0<br>0<br>0<br>‐5~~9 ‐4~~5<br>0<br>0<br>38<br>‐37<br>0<br>0<br>37<br>0<br>~~0~~<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>36<br>0<br>0<br>0<br>‐39<br>27<br>‐48<br>0<br>0<br>0|
|Serrano pepper|0<br>0<br>0<br>0<br>33<br>0<br>~~0~~<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>~~0~~<br>0<br>32<br>21<br>0<br>0<br>0<br>0<br>41<br>~~0~~<br>0<br>0<br>‐19<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>‐42<br>0<br>35<br>0<br>0|
|<br>Potato|0<br>0<br>0<br>19<br>0<br>0<br>0<br>0<br>0|
|Tomatillo|35<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>~~‐2~~4<br>0<br>0<br>0<br>0<br>0<br>0<br>35<br>~~3~~9<br>0<br>0<br>54<br>0<br>41<br>0<br>‐33<br>52<br>~~0~~<br>72<br>0<br>0<br>0<br>0<br>61<br>52<br>64<br>0<br>0<br>0<br>0<br>43<br>0<br>0<br>4~~9~~<br>53|
|Tomato ‐ beefsteak|0<br>0<br>0<br>‐50<br>0<br>‐3~~1 ‐3~~1<br>0<br>0<br>0<br>0<br>‐42<br>0<br>0<br>0<br>0<br>0<br>0<br>~~0~~<br>‐19<br>0<br>0<br>0<br>54<br>‐53<br>0<br>0<br>~~0~~<br>0<br>0<br>0<br>‐31<br>0<br>0<br>0<br>0<br>0<br>0<br>~~‐3~~0<br>0<br>0<br>‐84 ‐39<br>0<br>0<br>0|
|Tomato ‐ roma|0<br>25<br>0<br>0<br>0<br>0<br>~~2~~1<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>30<br>0<br>21<br>~~0~~<br>30<br>0<br>0<br>0<br>35<br>0<br>0<br>0<br>~~0~~<br>0<br>0<br>0<br>0<br>0<br>25<br>0<br>0<br>0<br>0<br>~~‐2~~7<br>0<br>0<br>0<br>0<br>0<br>‐2~~2~~<br>24|
|Zucchini|0<br>0<br>36<br>0<br>0<br>0<br>~~3~~6<br>‐41<br>0<br>‐4~~2~~<br>0<br>0<br>16<br>0<br>0<br>0<br>0<br>0<br>~~0~~<br>0<br>‐30<br>0<br>0<br>0<br>0<br>0<br>0<br>‐~~27~~<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>‐24<br>0<br>‐24 ‐78<br>0<br>0<br>0|
|Salt||
|Sugar ‐ 1kg pack|0<br>0<br>‐37<br>0<br>0<br>0<br>~~0~~<br>‐36<br>0<br>‐1~~9~~<br>0<br>0<br>0<br>‐14<br>0<br>~~0~~<br>0<br>‐38<br>0<br>0<br>0<br>‐~~57~~<br>0<br>0<br>‐31<br>0<br>0<br>0|
|<br>Sugar ‐ 2kg pack|0<br>0<br>0<br>0<br>95<br>0<br>‐32<br>0<br>0<br>0<br>‐3~~0~~<br>~~0~~<br>‐24<br>0<br>‐22<br>0<br>12<br>~~0~~<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>0|
|Cki il Mid|0<br>33<br>0<br>0<br>0<br>0<br>0<br>0<br>0<br>39<br>~~30~~<br>0<br>0<br>0<br>0<br>0|
|oong o ‐ xe<br>Cement ‐ 50kg bag|‐<br><br><br><br><br><br><br><br>‐<br>‐<br><br><br><br><br>|

26
# REGRESSION RESULTS

We exploit data granularity to estimate regressions of indicators at good-city-outlet level, which more are disaggregated than the indicators shown in the heat maps. First, we study which fixed effect characteristics of markets. Then, we run regressions to determine how markets respond to a large retailer’s entries and to COFECE sanctions.

# Fixed effect regressions

Fixed effects (FE) regressions provide another way to analyze how markets are behaving. Table 10 shows the amount of variation (R-squares) explained by each kind of fixed effects by themselves on pooled regressions that include all goods. For example, when running a regression of dispersion with only good fixed effects, these explain about 9% of the variation of such indicator. Following the same intuition, it can be seen that the characteristics of goods play an important role in explaining the variation of dispersion and volatility, something already seen in the heat map. City characteristics play a more important role in the magnitude of pass-through. Outlet-type fixed effects seem to be less relevant. We also notice that time fixed effects explain relatively little of the variation in dispersion and volatility. This means that these indicators do not change substantially throughout the time period covered by this series.

Table 10. R-squared values of fixed effect regressions

||Dispersion|Volatility|Differential|PT magnitude|PT speed|PT symmetry|
|---|---|---|---|---|---|---|
|Good FE|8.79%|51.35%|65.94%|1.19%|4.26%|4.26%|
|City FE|3.91%|2.66%|0.84%|3.77%|1.73%|1.20%|
|Outlet FE|1.46%|2.55%|1.40%|2.12%|0.72%|0.85%|
|Time FE|0.15%|0.45%|1.19%|‐‐|‐‐|‐‐|
|Total (sum)|14.31%|57.02%|69.36%|7.08%|6.71%|6.31%|

R‐squared of fixed effect regressions containing **only** the controls described in each row. The row "Total (sum)" is for illustrative reasonsonly, asit adds the r‐squareds of separate FE regressions and does not necessarilycoincide with pooled FE regressions containing all of these controls.

Fixed-effects specifications. We also estimate fixed effect regressions with several types of dummies, as opposed to the results shown in the table above. These specifications are intended to associate differences in the patterns of indicators to markets across time periods in a more precise way. Our specifications include City, Good, Outlet and Time dummies in order to analyze their relevance in explaining the variation of the behavior of each of the three price indicators—dispersion, pass-through and volatility.

Equation (7) is the pooled specification we estimate. Variable y denotes the indicator that is being regressed and subscripts g, c, o, t refer to varieties of good, city, outlet and time periods, respectively. Variables d denote dummies for each category.

27
Table 11. City fixed effects results

||(1)|(2)|(3)|(4)|(5)||
|---|---|---|---|---|---|---|
||Dispersion|Volatility|PT magnitude|PT speed|PT asymmetry||
|**City FE (Mexico City ex**|**cluded)**||||||
|Mexicali|‐3.017***|2.120***|‐0.054***|0.156***|0.023***|N|
|Tijuana|‐2.569***|1.772***|0.052***|0.162***|0.049***|ort|
|La Paz|‐1.514***|0.621***|‐0.170***|0.175***|0.008|hern|
|Cd. Acuna|‐2.107***|1.230***|0.021*|0.056***|‐0.030***|bo|
|Cd. Juarez|‐1.433***|0.537***|‐0.057***|0.090***|‐0.026***|rde|
|Matamoros|‐1.962***|1.651***|0.009|0.094***|0.080***|r|
|Tepic|‐3.247***|0.164*|‐0.025***|0.098***|‐0.005|No|
|Culiacan|‐3.741***|0.861***|‐0.003|0.079***|0.014*|rth|
|Hermosillo|‐2.412***|1.670***|0.013|0.176***|0.027***|wes|
|Huatabampo|‐3.673***|1.120***|‐0.158***|0.204***|0.079***|t|
|Torreon|‐2.440***|2.037***|‐0.023***|0.084***|0.023***||
|Monclova|1.807***|‐0.205*|‐0.088***|0.007|‐0.077***||
|Chihuahua|‐0.911***|‐1.189***|‐0.067***|0.060***|0.092***|N|
|Jimenez|‐4.066***|1.400***|0.061***|0.117***|0.079***|orth|
|Durango|‐3.174***|1.361***|‐0.009|0.084***|0.130***|eas|
|Monterrey|‐0.924***|2.123***|0.051***|0.078***|0.001|t|
|Tampico|‐1.968***|1.897***|‐0.167***|0.122***|‐0.014***||
|Fresnillo|‐6.696***|0.719***|0.004|0.146***|0.058***||
|Aguascalientes|‐2.149***|0.979***|‐0.009|0.081***|0.006||
|Colima|‐3.848***|‐1.226***|‐0.049***|0.091***|‐0.036***||
|Leon|‐2.624***|0.639***|‐0.067***|0.051***|0.025***||
|Cortazar|‐6.113***|‐0.501***|‐0.031***|0.056***|‐0.058***|Cen|
|Guadalajara|‐1.109***|‐0.142***|‐0.030***|0.038***|0.008*|ter‐|
|Tepatitlan|‐9.216***|‐0.400***|‐0.058***|0.079***|‐0.033***|No|
|Morelia|‐4.830***|0.408***|‐0.038***|0.105***|0.056***|rth|
|Jacona|‐8.472***|‐0.685***|‐0.071***|0.056***|‐0.089***||
|Queretaro|‐3.014***|0.747***|‐0.042***|0.103***|0.011*||
|San Luis Potosi|‐3.310***|1.210***|0.067***|0.083***|0.040***||
|Acapulco<br>|‐3.169***<br>|‐0.364***<br>|‐0.027***<br>|0.074***<br>|0.034***<br>||
|Iguala|‐6.064***|1.174***|‐0.032***|0.179***|0.118***||
|Tulancingo|‐6.413***|‐0.530***|‐0.058***|0.050***|0.074***||
|Toluca|‐2.362***|‐0.328***|‐0.057***|0.078***|‐0.022***|Ce|
|Cuernavaca|‐5.639***|0.712***|‐0.061***|0.113***|0.028***|nter|
|Puebla|‐3.033***|0.187***|0.040***|0.062***|0.028***|‐So|
|Tlaxcala|‐4.991***|‐0.074|0.027***|0.109***|0.039***|uth|
|Veracruz|‐3.393***|0.134|‐0.099***|0.091***|0.035***||
|Cordoba|‐2.456***|‐0.663***|0.012*|0.054***|0.070***||
|San Andres Tuxtla|‐6.188***|‐1.218***|‐0.058***|0.093***|0.009||
|Campeche|‐2.991***|‐0.353***|‐0.087***|0.081***|0.048***||
|Tapachula|‐4.030***|‐0.534***|‐0.152***|0.136***|0.065***||
|Oaxaca|‐3.405***|0.752***|‐0.048***|0.135***|0.034***|S|
|Tehuantepec|‐4.617***|‐0.702***|‐0.086***|0.156***|0.117***|out|
|Chetumal|‐5.892***|1.248***|‐0.235***|0.133***|0.056***|h|
|Villahermosa|‐3.988***|‐0.648***|‐0.071***|0.091***|0.051***||
|Merida|‐0.039|0.744***|‐0.082***|0.083***|0.046***||
|Constant|15.264***|4.343***|0.178**|0.284***|0.022||
|Observations|412,017|663,508|4,475|4,475|4,475||
|R‐squared|0.149|0.646|0.340|0.238|0.043||
|Clustered standard err|ors by city (not show|n in table). *** p<0|.01, ** p<0.05, * p<0.1||||
|Regressions include ad|ditional controls: Go|od FE, Outlet type F|E for all regressions; Tim|e FE for column|s (1) and (2).||

Tables 11 to 14 show fixed effect results of pooled regressions of the indicators studied in this paper. All regressions include additional controls than the ones shown in the tables, in order to obtain FE results after controlling for other factors that if omitted, may generate noise to the estimations.

28
Table 12. Good fixed effects results

||(1)<br>Dispersion|(2)<br>Volatility|(3)<br>PT magnitude|(4)<br>PT speed|(5)<br>PT symmetr||
|---|---|---|---|---|---|---|
|**Good FE (Rice excluded)**|||||||
|Beans|5.177***|2.287***|0.359***|‐0.129***|0.128|Grain|
|Eggs ‐ per piece|‐6.342***|4.565***|0.197**|‐0.180***|‐0.070|E|
|Eggs ‐ 12 pack|‐7.624***|1.547***|‐0.026|0.067|0.021|ggs|
|Eggs ‐ 18 pack|‐5.881***|1.465***|‐0.055|‐0.020|0.339*|&|
|Eggs ‐ 30 pack<br>|‐6.128***<br>|3.262***<br>|0.079|‐0.101*|0.082|diary|
|Milk|‐5.400***|‐2.132***|‐‐|‐‐|‐‐||
|Bolillo bread|‐2.454|‐1.855***|‐‐|‐‐|‐‐|Br<br>t|
|Concha bread|‐0.581|‐1.072***|‐‐|‐‐|‐‐|ead<br>ortil|
|Corn tortillas|‐4.979***|‐1.039***|0.179|‐0.242***|0.038|&<br>la|
|Water ‐ 1lt bottle<br>Water ‐ 1.5lt bottle|‐3.842***<br>‐2.847**|0.415<br>‐1.186***|‐‐<br>‐‐|‐‐<br>‐‐|‐‐<br>‐‐|Beve|
|Soda ‐ 2lt bottle|‐3.863***|‐0.470|‐‐|‐‐|‐‐|rage|
|Soda ‐ 600ml bottle|‐6.574***|‐1.371***|‐‐|‐‐|‐‐|s|
|Beef ‐ chop|‐0.773|0.463|0.345***|‐0.149***|0.044||
|Beef ‐ ground<br>|2.889**<br>|1.322***<br>|0.541***<br>|‐0.185***<br>|0.096<br>||
|Beef ‐ rib|1.151|1.066***|0.483***|‐0.138***|0.131*||
|Beef ‐ steak|‐2.475***|0.692**|0.455***|‐0.195***|0.066|M|
|Chicken ‐ whole|‐3.867***|2.938***|0.933***|0.013|0.092|ea|
|Chicken ‐ breast|‐1.539|2.504***|0.988***|0.071|0.125|t|
|Chicken ‐ roasted|‐0.852|‐0.734**|0.627***|‐0.046|0.074||
|Pork ‐ rib|2.093**|0.805**|0.163**|‐0.117***|0.055||
|Pork ‐ steak|‐4.404***|1.411***|0.118|‐0.107**|0.086||
|Apple|‐0.020|6.752***|0.308***|0.062|0.043||
|Banana|2.086**|10.257***|1.022***|‐0.060*|0.061||
|Guava|0.757|7.667***|‐‐|‐‐|‐‐||
|Lime|0.774|16.107***|0.271***|‐0.225***|‐0.004||
|Muskmelon|1.188|13.603***|0.247***|‐0.003|0.024|Fr|
|Orange|2.056**|12.744***|0.163**|‐0.171***|‐0.019|uits|
|Papaya|‐0.220|10.321***|0.387***|‐0.049|‐0.053||
|Pear|‐1.835**|6.472***|0.163**|‐0.062|‐0.006||
|Pineapple|‐0.893|9.226***|0.028|‐0.133***|0.032||
|Plantain<br>Watermelon|‐2.169**<br>1.678*|3.825***<br>13.346***|0.340***<br>0.158**|0.012<br>0.040|0.051<br>0.056||
|Avocado|‐0.101|9.546***|0.745***|‐0.122***|‐0.042||
|Cabbage|4.590***|8.601***|0.127|‐0.029|0.086||
|Carrot|1.044|8.809***|0.209***|‐0.041|0.031||
|Chayote|2.438**|14.167***|0.401***|0.021|‐0.048||
|Cucumber|0.616|16.188***|0.137*|0.020|‐0.097||
|Lettuce|0.530|9.937***|‐0.004|0.072**|0.094||
|Onion|3.564***|14.935***|0.217***|‐0.216***|0.067|Veg|
|Jalapeno pepper|0.484|13.548***|0.515***|0.179***|‐0.046|eta|
|<br>Poblano pepper|0.255|14.193***|0.573***|‐0.033|0.043|bles|
|Serrano pepper|1.233|13.552***|0.466***|0.035|0.024||
|Potato|0.714|9.731***|‐0.060|‐0.084*|0.072||
|Tomatillo|0.867|14.418***|0.553***|‐0.018|‐0.106*||
|Tomato ‐ beefsteak|1.672*|20.217***|0.290***|0.084*|0.042||
|Tomato ‐ roma<br>Zucchini|3.369***<br>2.791***|19.924***<br>17.311***|0.212***<br>‐0.024|‐0.043<br>0.009|‐0.008<br>0.034||
|Salt|‐0.065|‐2.239***|‐‐|‐‐|‐‐||
|Sugar ‐ 1kg pack|‐3.706***|0.646*|0.316***|‐0.133***|0.104||
|Sugar ‐ 2kg pack|‐2.990***|0.202|0.368***|‐0.186***|‐0.056|Othe|
|Cooking oil ‐ Mixed|‐6.371***|‐0.667**|0.062|‐0.030|0.085|r|
|<br>Cement ‐ 50kg bag|‐10.822***|‐3.395***|‐‐|‐‐|‐‐||
|Constant|15.264***|4.343***|0.178**|0.284***|0.022||
|Observations|412,017|663,508|4,475|4,475|4,475||
|R‐squared|0.149|0.646|0.340|0.238|0.043||
|Clustered standard errors by|city (not shown in t|able). *** p<0.01, *|* p<0.05, * p<0.1||||
|Regressions include addition|al controls: City FE,|Outlet type FE for al|l regressions; Time FE|for columns (1) an|d (2).||

29
The results of city fixed effects regressions are provided in Table 11. The excluded city in this case is the capital. Some clear patterns emerge. In terms of price dispersion, prices in Mexico City exhibit more dispersion in general and lower dispersions tend to be concentrated in cities in central states. This finding is not surprising since it is likely that our definition of markets, in a large city like Mexico City includes many markets. As stated before, our empirical definition of markets was likely to be more aggregated than one using cross-price elasticities would have determined.

Also, cities with more volatile prices tend to be located in the north. The magnitude of passthrough in Mexico City is generally higher than in most cities, but the speed of adjustment is lower.

The characteristics of goods matter in understanding other aspects in the functioning of markets. Goods that are less perishable and easier to transport, such as beverages, cement, salt, sugar and eggs have the lowest dispersions after controlling for other factors. In contrast, fruits and vegetables exhibit similar or relatively higher dispersion than rice, the excluded term. As suggested by the heat maps, the most volatile prices are for fruits and vegetables, while prices for meat are the most sensitive to changes to international prices.

Table 13 displays the results of the outlet FE regressions. Dispersion and volatility in supermarkets are in general higher than in other types of stores, but also in turn absorb shocks of international prices to a greater extent and at a more rapid pace. Table 14 shows semester FE results. This was done in order to identify how dispersion and volatility have evolved through time. The results indicate that dispersion is modestly increasing. Coefficients are relatively small but significant. Dispersion has increased by less than 1%. Volatility has been comparatively more stochastic across time; the coefficients suggest that volatility has decreased slightly by the end of the period.

Table 13. Outlet fixed effect results

||(1)<br>Dispersion|(2)<br>Volatility|(3)<br>PT magnitude|(4)<br>PT speed|(5)<br>PT symmetry|
|---|---|---|---|---|---|
|**Outlet** **FE** **(Supermarke**|**t** **excluded)**|||||
|Specialized store|‐1.911***|‐4.834***|‐0.096***|‐0.071***|‐0.074***|
||(0.452)|(0.305)|(0.026)|(0.015)|(0.018)|
|Public market|‐3.041***|‐5.240***|‐0.102***|‐0.062***|‐0.071***|
||(0.437)|(0.309)|(0.015)|(0.011)|(0.015)|
|Convenience store|‐1.671***|‐4.080***|‐0.064**|‐0.049***|‐0.051**|
||(0.458)|(0.346)|(0.024)|(0.017)|(0.023)|
|Informal market|‐2.228|‐4.452***|‐0.134***|‐0.012|‐0.044*|
||(1.403)|(0.626)|(0.024)|(0.028)|(0.022)|
|Warehouse club|‐3.212***|‐4.373***|‐‐|‐‐|‐‐|
||(0.704)|(0.612)|‐‐|‐‐|‐‐|
|Constant|15.264***|4.343***|0.178**|0.284***|0.022|
||(0.793)|(0.278)|(0.069)|(0.039)|(0.062)|
|Observations|412,017|663,508|4,475|4,475|4,475|
|R‐squared|0.149|0.646|0.340|0.238|0.043|

Clustered standard errors by city in parentheses. *** p<0.01, ** p<0.05, * p<0.1 Regressions include additional controls: City FE, Good FE for all regressions; Time FE for columns (1) and (2).

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Table 14. Semester fixed effect results

|(1)|(2)<br>|
|---|---|
|Dispersion|Volatility|
|**Semester** **FE** **(First** **available** **semester** **excluded)**||
|2010 ‐ 2nd semester<br>0.007|‐‐|
|(0.100)|‐‐|
|2011 ‐ 1st semester<br>0.492***|0.393***|
|(0.113)|(0.076)|
|2011 ‐ 2nd semester<br>0.487***|0.174|
|(0.159)|(0.146)|
|2012 ‐ 1st semester<br>0.235|‐0.297**|
|(0.147)|(0.127)|
|2012 ‐ 2nd semester<br>0.449***|‐0.694***|
|(0.152)|(0.135)|
|2013 ‐ 1st semester<br>0.702***|‐0.142|
|(0.166)|(0.160)|
|2013 ‐ 2nd semester<br>0.606***|0.231|
|(0.184)|(0.141)|
|2014 ‐ 1st semester<br>0.787***|0.716***|
|(0.206)|(0.155)|
|2014 ‐ 2nd semester<br>0.574***|‐0.413**|
|(0.208)|(0.166)|
|2015 ‐ 1st semester<br>0.841***|‐0.095|
|(0.229)|(0.186)|
|2015 ‐ 2nd semester<br>0.685***|‐0.861***|
|(0.214)|(0.197)|
|Constant<br>15.042***|5.394***|
|(0.823)|(0.322)|
|Observations<br>412,017|663,508|
|R‐squared<br>0.148|0.645|
|Clustered standard errors by city in parentheses.<br>*** p<0.01, ** p<0.05, * p<0.1||
|Regressions include additional controls: City FE, Good|FE and Outlet type FE|

# Market structure and competition regressions

The tables that follow contain the results of the effects of the large retailer’s entries and COFECE sanctions on market efficiency. We include the results of split regressions by goods groups and geographical regions to have a clearer idea of how markets might be responding to such variables.

Specifications related to the large retailer’s store entries. We use the cumulative entries of stores since the beginning of the period of study to measure the effect of the large retailer in Mexican markets. Equation (8) shows the specification, which also includes FE dummies. This means that the value of variable large retailer indicates the total of openings in city c until time period t. We have the possibility of running regressions using the large retailer’s third brand store entries only, the first brand stores entry only, or the effect of any of the large retailer’s brand stores entering in markets. In regressions where dependent variables are pass-through indicators, the variable large retailers refers to the total openings of stores by city during the period of study. This is because pass-through indicators are calculated for the complete period 2010-2015 and thus do not allow for time variation.

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54 46 6 144 Vgcot = & + B Walmex,, + », Ngdg + >, V¥ed- + >, 6,d, + », Ards + Egeot g=1 c=1 o=1 t=1
Table 15 shows the results of large retailer’s entries in cities.<sup>12</sup> In the pooled regression (i.e. in the “National” and “All goods” cell in the table), it seems that price dispersion is not affected by having additional stores in the markets of cities. Split regressions show that price dispersion is reduced after the large retailer’s stores are opened for some goods or regions. This is especially the case for the Center-South region and for grains in some areas.

The large retailer’s apparent lack of effect in price dispersion might seem to be puzzling, but it is important to have in mind that these regressions estimate the effect of the large retailer in different markets within a city, that is, indicators at the triad-level of good-city-outlet. Thus, it is possible that a new large retailer store in a city might have dissimilar effects in its different markets: it might affect price dispersion in supermarkets, but perhaps not too much in convenience stores, for example. However, the large retailer appears to have a greater effect in lowering dispersion at city level markets (i.e. dispersion of prices irrespective of type of store).<sup>13</sup> The effect of the large retailer’s entry on price volatility is more noticeable. On average, the large retailer’s stores reduce volatility, which means that prices tend to be more stable in markets within a city (as well as at city level). The effect is more general in northern cities and in the capital. Perishables are the most affected goods.

As expected, the extent of price transmission (pass-through magnitude) increases when the large retailer enters a market. This effect is greater in the North. The speed of adjustment seems to be reduced, but this seems to be driven by stores in Mexico City.

Specifications related to changes in market competition. We construct a dummy variable, COFECEgc, valued zero in time periods before a sanction and one after the sanction. Dates of sanctions vary by industry, (i.e. the type of good), which means that zero and one values differ by good. Equation (9) shows the specification used. Only goods affected by a COFECE sanction were included in regressions, thus, the interpretation of results should be seen as a before/after exercise. Pass-through regressions were not estimated for COFECE sanctions, due to the lack of time variation in pass-through indicators.

Table 16 shows the results of COFECE sanctions. In general, dispersion and volatility are reduced after COFECE fines businesses. This implies that COFECE sanctions are effective and indeed seem to be correcting competition problems in some extent. However, when analyzing regressions by good type, effects seem to vary, suggesting that the effect of fines may vary by industry.

> 12 We present the results of entries of Wal-Mart supercenters only (not other types such as Aurrerá or Superama), but results with complete Walmex stores or Aurrerá stores are very similar to Wal-Mart entries.

> 13 Regressions not shown in document. The specifications are exactly as regressions at good-city-outlet level, but for more aggregated indicators at good-city level only.

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Table 16. Effect of COFECE sanctions

||All goods<br>affected by<br>sanctions|Eggs|Tortilla|Soda|Poultry|Avocado|Cement|
|---|---|---|---|---|---|---|---|
|Dependent variable: Pric|e dispersion|||||||
|National|‐0.560**|‐0.671|‐0.617*|‐0.182|0.867**|0.770**|‐0.025|
|Northern border|0.000|0.571|0.235|1.410|‐0.165|1.292|0.121|
|Northwest|‐2.067*|‐0.360|‐0.753|1.374|1.001|1.011|‐0.931***|
|Northeast|‐0.913|‐0.807|0.685|‐0.597|0.533|1.205|0.254|
|Center north|‐0.337|‐0.809**|‐1.098**|‐0.101|0.953|0.026|0.012|
|Center south|‐1.108**|‐0.093|‐0.795|‐1.222|0.297|1.448|‐1.910***|
|South|0.729|‐3.058*|‐1.956***|‐2.569|2.372|‐0.466|0.000***|
|Mexico City|‐0.354|‐0.725***|‐1.284***|1.330***|1.840***|‐0.123|1.189***|
|Dependent variable: Pric|e volatility|||||||
|National|‐1.205***|‐1.979***|‐1.086***|‐0.288|0.140|‐1.600***|‐0.498***|
|Northern border|‐0.814*|‐1.084**|‐0.768**|‐1.010|‐0.225|‐0.835*|‐0.536|
|Northwest|‐0.832|‐0.261|‐1.390|0.383|‐0.471|‐1.051|‐0.778|
|Northeast|‐1.376***|‐2.497***|‐0.967***|‐0.050|0.448|‐1.802**|‐0.243|
|Center north|‐1.240***|‐1.731***|‐1.139***|‐0.194|0.388|‐1.563**|‐0.313|
|Center south|‐1.426***|‐2.654***|‐1.239***|‐0.326|0.098|‐2.359***|‐0.598*|
|South|‐1.184***|‐1.920**|‐1.044***|‐0.844|‐0.019|‐1.736*|‐0.729*|
|Mexico City|‐0.586***|‐1.675***|‐1.150***|‐0.687***|0.751***|‐1.469***|‐0.919***|

Clustered standard errors by city (not shown in table). *** p<0.01, ** p<0.05, * p<0.1 The table presents the results of split regressions by good groups and geographical regions. Each cell contains the coefficient β of the respective split regression according to Equation (9). β captures the effect of the COFECE sanction on the dependent variable after controlling for good, city, outlet and period FE.

# CONCLUSIONS

Our goal in this descriptive study was to develop and explore a set of measures to examine the relative efficiency (functioning) of markets by looking at the behavior of prices for wellspecified commodities. We examined the behavior of outlet-level retail prices for common commodities sold throughout Mexico in order to understand the functioning of markets. This examination of prices was done by looking at three main indicators; namely, price dispersion, price volatility, and price transmission (speed, completeness and symmetry). Once we designed the indicators, we provide patterns and conditions for each across commodities, regions and time. Depending on the indicator, we found clear regional and commodityspecific effects. In other words, some commodities were inherently more volatile than others in most regions of Mexico and some regions were inherently more volatile when we analyzed the behavior of a specific commodity.

We then used fixed effects models to more precisely identify the extent to which commodity, location, outlet, and temporal variation explain the behavior of these price indicators. The results of these models confirmed what the descriptive statistics showed; namely, while there is heterogeneity across products, locations matter tremendously. So, the price conditions and trends of something quite common like maize can vary across locations and outlets. In sum, there is a need to better understand these patterns and we can conclude that Mexico is not one, well-integrated national market if we use these indicators to guide us.

Finally, we tested whether we could predict changes in these indicators (increased efficiency) by looking at three changes expected to have a positive effect on the functioning of markets; changes in competition and the entry of the large retailer’s stores into the local retail market.

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We showed that these changes did in fact affect the changes in the proposed market efficiency indicators in the way theory would predict. This supports our assertion that these indicators are likely to be good benchmarks to assess the relative efficiency (functioning) of markets.

While validating the indicators developed to test whether they behave as theory would predict with the entry of the large retailer, another important finding should not be lost; namely, the large retailer’s entry into retail markets seems to lower prices and therefore likely increases economic welfare. While our findings are suggestive, and our goal was never to test this hypothesis with the kind of rigor that it merits, this indicative finding supports the work of Atkin et al (2016).

For policy makers concerned about how changes in policies translate to prices paid by vulnerable groups or in poorer areas, the findings of this study provide support for efforts to monitor markets through the use of these indicators. For example, for policy makers worried about the distributional effects of liberalizing trade, they can usefully benefit from examining these micro-level price indicators to help them identify and understand the challenges certain markets may face, and to design, target and evaluate the effectiveness of efforts to help groups of people and households that transact in markets and locations most negatively affected by changes in policies. In addition, these indicators provide information about relative competition levels. Competition authorities can test and develop these indicators further and use them in their arsenal to monitor relative competition as a first, cursory assessment of competition. Doing this may save these authorities a lot of time and effort and possibly make them more effective. A yet to be published paper by Falcao Bergquist (2016) also suggests that competition among traders (or lack thereof) has similar traces with respect to price behavior in for maize in Kenya.<sup>14</sup> In conclusion, the big message of this research is about the heterogeneity of how markets function, even for common and well-defined products. There are clear, non-random patterns to the behavior of these indicators. This is sobering because the singular focus of macro-level statistics on such things as price stability (a very worthy aim) may mask a lot of variation on the micro-level behavior of prices.

> 14 Falcao Bergquist, L (2016) Pass-through, competition and entry in agricultural markets: Experimental evidence from Kenya, Job Market Paper.

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