Introduction
The effect of wages on inflation has been a foremost subject of interest in economics. According with the traditional theory, the costpush or the markup price function explain how wages increases are transferred into prices. It seems worth researching and testing this tenet empirically. In this regard, during the 19501960’s substantial studies were made by ^{Phillips (1958)}, ^{DicksMireaux and Dow (1959)}, ^{Klein, Ball, Hazlewood and Vandome (1961)}, and ^{Lipsey and Steuer (1961)}. Continuation over similar research lines are presented in ^{Stigler (1966)}, ^{Rotemberg (1987)}, ^{Merton and Upton (1988)}, ^{Hall and Taylor (1989)}, ^{Ball and Mankiw (1995)}, ^{Romer (1996)}, ^{Pujol and Griffiths (1997)}, ^{Varian (1999)}, ^{Galí and Gertler (1999)}, ^{Woodford (2003)}, ^{Christiano et al., (2005)}, ^{Uhlig (2005)}, ^{Galí et al., (2007)}, ^{Galí (2008)}, ^{Coibion and Gorodnichenko (2013)}, ^{Mankiw (2015)}, ^{Féve and Sahuc (2017)}, and ^{Cantore et al., (2021)}.
This paper contributes to the analysis of the effect of wages on inflation in Mexican manufacturing. A markup price function econometric test is performed to gauge this effect. Besides, a twoperiod comparison, i.e., 19942003 and 20072016 is performed. An error correction econometric model is used with monthly frequency. The first period starts with the enactment of the North America Free Trade Agreement (NAFTA). A second period is associated with the beginning of the Great Recession. The econometric results could provide useful inference about the inflationary nature of wages in the Mexican case^{1}.
Manufacturing wage performance is gauged using an error correction model for the abovementioned sets of periods. A first equation deals with wages and bilateral nominal exchange rate impacts on producer inflation. A second equation measures producer price index, bilateral nominal exchange rate, and wage effect on consumer inflation. These equations follow the work of ^{Pujol and Griffiths (1997)}, who use an error correction model and Granger causality tests to estimate the econometric relationships embedded in the markup price function. The Granger causality tests results are an informed guided to equation specification.
The error correction model results could prove or discard theoretical tenets, in this case, regarding the empiric effect of wages on inflation. The implementation of this kind of model is suitable, when there is a lack of specific data generating models in the body of traditional theory^{2}.
In this paper, wages are represented by the nominal average production wages per person for the whole manufacturing sector. The manufacturing production price index without oil represents a weighted measure of intermediary inputs costs^{3}. The consumer price index gauges the finished goods price change. The bilateral nominal exchange rate between Mexico and the United States represents an adjustment price in an open economy, with imperfect competition and asymmetric information^{4}.
Questions represented by income policies, rational expectations, the Phillips curve identification, quantitative equation, structural changes, Penn effect and their testing are beyond the scope of this research. These problems have been dealt with extensively in the literature. Evidence of these issues can be found in ^{Chow, 1960}; ^{Lucas, 1972}; ^{Wallis, 1979}; ^{Desai, 1975}; ^{Henry and Ormerod, 1978}; ^{Samuelson, 1994}; ^{Lucas, 1996}; ^{Melnick and Strohsal (2017)}, for instance.
This paper is organized as follows. Section I presents a brief literature review, where theoretical models place wages as an inflationary source. The second section presents a nonparametric data assessment by means of descriptive statistics. Besides, a figure comparison is presented for both periods under analysis, i.e., 19942003 and 20072016. Section III proposes an econometric model based on an error correction model. The econometric model is applied for Mexican manufacturing, for these two periods. Section IV examines the econometric results. Finally, the conclusions recount the empirical findings and their statistical inference.
I. Brief literature review
The inflationary nature of wages is often examined through the standard costspush price formation model. Modifications of this basic model results on different models, i.e., the markup price function and inflation wageprice spirals. On one hand, the short and long term costspush and markup price functions imply that, in presence of money neutrality, production costs increases are transferred fully into output prices (^{Rotemberg, 1987}). On the other hand, short term wageprice spiral function assumes price rigidities, where production costs increase is sluggishly transferred into output prices^{5}.
As a modification of the costspush model, the markup price function formalizes the relationship among wages, producer, and consumer prices. In the New Keynesian framework, a costspush model is represented by a onetime shock in marginal costs. These costs could be measured through labor costs, the markup, or both. According with ^{Coibion and Gorodnichenko (2013)}, New Keynesian models suggest that marginal costs are a relevant source of inflationary pressures. In the New Keynesian Phillips curve labor income share is used as a proxy for marginal costs, where it could affect real quantities like the Gross Domestic Product (^{Woodford (2003)}, ^{Galí and Gertler (1999)}). ^{Galí (2008)} assumes perfect labor mobility, while capital is fixed and normalized to one.
The aggregate economic activity is examined by New Keynesians using micro foundations. In the case of ^{Christiano et al. (2005)}, wage contracts have a key role in nominal price rigidities. These rigidities could account for inertial responses in inflation, and a persistent response in output. For instance, ^{Romer (1996)} considers a shortterm markup price function composed by sticky wages and flexible output prices. Under imperfect competition and asymmetric information his markup function is represented as follows:
where
Continuing with ^{Romer (1996)}, the dynamics to establish a longterm markup price function considers wages at time
where
To evince the dynamics on equation (2) consider an inflationary trigger at
The above inflationary trigger implies for equations (2)’ and (2)’’ that
In general equation (3) can be expressed as
in the expression above
equation (3)’’ implies that changes in
^{Pujol and Griffiths (1998)} present a variation of the previous markup price function, as follows:
where
^{Pujol and Griffiths (1998)} consider that output affects prices through at least two distinct channels. The first one is related with marginal costs. For example, with increasing returns to scale and holding factor prices constant, marginal costs would decline as output increases. The second channel is through the effect on the markup effect. According with equation (4) if the markup (
^{Merton and Upton (1988)} and ^{Stigler (1966)} present similar costspush tenets. For their part, ^{Hall and Taylor (1989)} consider price formation as a positive constant time marginal cost. An analysis of the inflationary wageprice spiral is made by ^{Blanchard (1993)}. Independently, ^{Ball and Mankiw (1995)} set prices as a markup over marginal costs under a monopoly environment. Similar positions are held by ^{Varian (1999)}, as well as ^{Mankiw (2015)}.
The above literature review presents price formation models based on costspush model modifications. On one hand, wages are an important component of production costs. The longterm dynamics of the model is expounded by two possible outcomes: an increase in production costs is transferred into output prices; or factor prices increases cancel out leaving real quantities without change. On the other hand, the markup is assumed to be payment for capital use, financial services, and depreciation costs. In brief, net domestic product after labor costs. Capital production input is an exogenous variable on the markup function. In this paper, only endogenous variables are dealt with in the econometric analysis. As a result, capital factor costs are not considered to be part of this research.
II. Data description
Descriptive statistics
The 19942003 data is taken from Encuesta Industrial Mensual (EIM), which comprises 205 industrial activities. The 20072016 data come from Encuesta Mensual de la Industria Manufacturera (EMIM), which copes with 240 industrial activities. These two surveys differ in time availability, methodologies, and industrial activities^{8}. Therefore, they are addressed individually. The first period is related with the enactment of the North America Free Trade Agreement (NAFTA). The second period is associated with the beginning of the Great Recession.
On table 1 the summary statistics of the time series used in this research are reported. These time series comprise: Mexican manufacturing wages, producer and consumer price indexes and bilateral nominal exchange rate for the periods of 19942003 and 20072016. The summary statistics are the mean (Mean), standard deviation (SD), kurtosis (KT), and the coefficient of variation (CV). The purpose of table 1 is the description of the data principal trends.
Indicator  Statistic  Periods  

1994:012003:02  2007:012016:06  
wages  Mean  3.10  5.13 
SD  1.35  0.64  
KT  2.61  3.99  
CV  0.44  0.12  
producer price index  Mean  44.68  94.14 
SD  15.16  10.03  
KT  1.90  2.26  
CV  0.34  0.11  
consumer price index  Mean  47.45  102.18 
SD  17.20  10.91  
KT  1.74  1.81  
CV  0.36  0.11  
bilateral nominal exchange rate  Mean  8.14  13.18 
SD  2.00  1.90  
KT  3.78  4.02  
CV  0.25  0.14  
n  110  114 
Note 1. Wages stand for nominal average wages per production worker for Mexican manufacturing as a whole; producer price index stands for manufacturing producer index excluding oil; bilateral nominal exchange rate represents Mexican pesos per U.S. dollar. All variables are in levels. Detailed explanations for units and base years are reported in Appendix 2. Note 2. 1994:012003:02 stands for January 1994 to February 2003; 2007:012016:06 stands for January 2007 to June 2016, and n is the number of observations.
Source: Own estimates based on Instituto Nacional de Geografía y Estadística (INEGI).
In table 1, nominal wages Mean has increased from 3.10 to 5.13. Meanwhile their SD has decreased from 1.35 to 0.64. Their KT has increased towards the second period e.g., from 2.61 to 3.99, denoting a higher wage process persistence^{9}. Wages reduce their volatility throughout time, as its CV decreases from 0.44 to 0.12 for the 19942003 and 20072016 periods, respectively. This CV value indicate that wages dispersion decreased around the mean.
For its part, manufacturing producer price index has Mean values of 44.68, and 94.14 for each period, respectively. This increase indicates that the manufacturing producer price index has gain base points across time. Its SDs are 15.16 and 10.03 for each period, which points out to a decrease in volatility over time. Its KT increases over time, with values going from 1.90 to 2.26 for each period indicating a lesser variance in its process. Its CV decreases from the first period 0.34 towards 0.11 in the last period, which indicates that its process gains in stability.
The consumer price index Mean increases in base points over time from 47.45 to 102.18. Also, this index becomes more stable in its trend and structure for the last period. This stability is seen in its statistics: its SD decreases over time with values of 17.20 to 10.91 for each period under study, respectively. Its KT increases modestly over time, with values that go from 1.74 to 1.81 pointing out structural stability. Regarding its CV values they decrease from 0.36 on 19942003 to 0.11 on 20072016, which implies less volatility.
The bilateral nominal exchange rate between Mexican pesos per American dollar increases over time. This is a systematic fact regarding this nominal exchange rate between these two currencies. The nominal exchange rate has a mean value that goes from 8.14 to 13.18 in each period, respectively. Its SD decreases over time with values from 2.00 to 1.90 for each period, respectively. These values imply that the bilateral nominal exchange rate has a decrease in volatility. For its part, its KT increases over time with values that go from 3.78 to 4.02 denoting an increase in its persistence. Its CV remains without much change on both periods, e.g., 0.25 and 0.14, denoting a higher stability.
Figure analysis
In what follows, a figure analysis on annual growth rates is performed for the time series reported on table 1. The following figures represent annual growth rates, which are computed on an annual basis: month yearonmonth year percentage change. One year of observations in both periods is lost because of the annual growth rates computation.
Left panels represent the period of 19952003, and the right panels depict the period 20082016. Figure 1 contains two panels depicting the same pair of variables for each period. This arrangement facilitates graphic annual growth rates comparison among periods.
Panels a and b on Figure 1 display producer and consumer inflation for the periods of 19952003 and 20082016, respectively. Panel (a) shows that producer and consumer inflation move almost hand by hand. The differences in Mean and SD for these two variables do not allow seeing this parallelism. However, their KT and CV values do because they do not have units. Therefore, they can be applied to annual growth rates description without unit problems. These statistics values are similar: 1.90 vs. 1.74 for KT, and 0.34 vs. 0.36 for CV, for each period. The high inflation depicted during 1995 could be linked with the Mexican peso devaluation of 1994. This last events account for the large axis size on panel (a). As a result, panel a registers inflation around the 60 points. Panel (b) scales do not overpass the 11 points. If, there was a lens in panel (a) around the 10 points scale, then it could be seen that there is a continuation of the producer and consumer inflation scales from period to period. The changes in scale could made the data look different across periods. Panel (b) shows almost two trends between consumer and producer inflations: simultaneity until 2009, 2011 and 2012; and only inverse for the last year.
In Figure 2, Panels (c) and (d) display producer inflation and bilateral nominal exchange rate for the periods of 19952003 and 20082016, respectively. In both panels, these time series move almost in parallel way. Also, it seems that during the first and second periods there is a positive relationship between producer inflation and the bilateral exchange rate.
Panel (e) and (f), figure 3, show that wages have a positive relationship with respect to consumer inflation. Similar figures could be observed if wages and producer inflation were plotted^{10}. During the period from 1995 to 2003 the growth of wages is modest with respect to consumer inflation. This behavior is reverted during the last period of 2008 to 2016, where it seems that there is less variance between wages and consumer inflation.
III. Methodology
An error correction model is applied to Mexican manufacturing. The comparison of the results is performed for two distinct periods, i.e., 19942003 and 20072016. Originally, this model was put forward by ^{Pujol and Griffiths (1998)} for the Polish economy. It has been followed by other authors, i.e. ^{Carbajal (2003)}, ^{Stockhammer et al. (2009)}, ^{Onaran et al. (2011)}, ^{Onaran and Galanis (2014)}, ^{Onaran and Obst (2015)}. In the Pujol and Griffiths model local prices are a function of labor costs and import prices. It is based on a markup pricing model in an imperfect competitive economy. The theoretical part of Pujol and Griffiths model has been previously exposed in section I.
^{Sargan (1964)} explains that the error correction model departs from an empirical basis. His wageprice equations are tested by means of an error correction model. This author mentions that one of the best ways to prove traditional theory is using empirical tests. This is because there is a lack of data generating models that provide unicity between theory and empirics. Other authors who test theory through this empiric lens are ^{Hickman and Klein (1984)}, ^{Hendry and Wallys (1984)}, and ^{Spanos (1995)}. In the case of ^{Cantore et al., (2021)}, they mention that in a wider set of models there is a puzzling mismatch between data and theory. Being this the present paper case, then the error correction model is suitable to prove or discard theoretical tenets.
The longterm producer and consumer price indexes reduce form follows ^{Pujol and Griffiths (1998)} ^{11}:
where
Pujol and Griffiths explains that equation (5) measures the impact of the exchange rate on producer prices, since it affects the costs of import intermediate inputs. Also, the exchange rate may influence the markup of domestic firms: when the currency appreciates, margins shrink in those sectors most exposed to foreign competition.
Equation (6) is largely an account identity, as Pujol and Griffiths explain. This is in so far as it is a weighted average of producer price indices and import prices. Equation (6) incorporates wages since consumer goods are often more labor intensive than typical industrial goods. These authors mention that using exclusively the
The numbers above each equation (5) and (6), represent the long run reduced form hypotheses. According with the New Keynesians in the long run all prices are flexible, as express in equation (3)’’. Thus, the expected values for the estimators
Equations (5) and (6) keep an analogy to the wageprice core relationships on LINK models. These models basically study national macroeconomic equilibria. In this type of models, the economic equilibria are often denoted by accounting identities (^{Hickman and Klein, 1984)}. The shortterm error correction equations are:
where the symbol
The shortterm equations (7) and (8) are intended to gauge the inflationary effect of wages in producer and consumer inflation. The elasticities introduce producer and consumer inflations. Thus, equations (7) and (8) test wage inflationary effects on producer and consumer inflations.
IV. Results
The results reported on table 2 indicate that for the long term, there is a positive relationship between manufacturing producer price index, wages, and bilateral exchange rate in the long and short terms. In the long term the corresponding estimators are 0.48 and 0.64 for 19942003, and 0.35 and 0.46 for 20072016. For the shortterm equation (7), wage inflation effect on manufacturing producer inflation is almost nil, for both periods. That is to say,
independents(standard error)  dependent data  

equation 5  equation 7  
long term  short term  



19942003  20072016  19942003  20072016  

0.48(16.80)***  0.35(6.64)***  
19942003 
0.03(4.05)***  0.01(2.72)***  

0.64 (15.78)***  0.46 (10.10)***  
19942003 
0.04 (1.78)**  0.12 (10.00)***  

0.14 (8.77)***  0.03 (3.57)***  
c  1.92 (30.34)***  2.79 (31.73)***  0.01 (12.14)***  0.00 (7.88)*** 

0.96  0.79  0.57  0.50 
Akaike  2.18  3.13  6.45  8.10 
n  110  114  108  110 
Note: ***: 99% of statistical significance, **: 95% of statistical significance, *: 90% of statistical significance, n is number of observations.Source: Own estimations based on ^{INEGI} and ^{Banco de México (2021)}.
The results reported on table 3 indicate that for the
long term, equation (6) has a positive relationship between consumer and wage
inflations:
independents(standard error)  dependent data  

equation 6  equation 8  
long term  short term  



19942003  20072016  19942003  20072016  

0.10(10.15)***  0.07(3.37)***  
19942003 
0.01(5.14)***  0.01(2.22)***  

0.15 (11.71)***  0.14 (6.42)***  
19942003 
0.01 (1.67)***  0.04 (3.30)***  

1.05 (60.953)***  1.07 (33.12)***  

0.80 (26.97)***  0.25 (4.19)***  

0.19 (6.22)***  0.04 (1.47)**  
c  0.09 (2.72)***  0.01 (0.07)  0.00 (4.39)***  0.00 (9.05)*** 

1.00  0.98  0.89  0.31 
Akaike  5.62  5.28  8.18  8.07 
n  110  114  107  110 
Note: ***: 99% of statistical significance, **: 95% of statistical significance, *: 90% of statistical significance, n is number of observations.
Source: Own estimations based on ^{INEGI} and ^{Banco de México (2021)}.
The results reported on tables 2 and 3 do not comply with the hypothesis regarding flexible prices. Flexible prices imply that consumer and producer prices should have a unitary value at least in the long term. In contrast, the estimators reported on these tables provide insight of the presence of sticky prices in the short and long terms. In the short term the effect of wages and the bilateral exchange rate are close to nil for both periods. These results point out to a relatively weak role of wages in consumer and producer inflations. ^{Pujol and Griffiths (1998)} reach similar results in the short term where wage estimators are 0.06 and 0.20 with respect to producer and consumer inflations, respectively. According with ^{Gil Díaz and Ramos Tercero (1992)}, who examine the Mexican manufacturing sector wages are not inflationary. These authors even report negative elasticities from wages growth rate (1.924 for 1976:091982:01 and 1.762 for 1982:011987:03), while resorting to some key inflationary prices^{13}. In the case of the Euro Area, the United Kingdom, Australia, and Canada, ^{Cantore, et al., (2021)} mention that the relationship between the markup and the labor share, breaking down into a variety of models, which introduce aspects such as different production functions, fixed costs, labor market frictions, do not respond in the way models predict.
In the short term, it seems that import prices are sticky. The bilateral nominal exchange rate estimators with respect to producer and consumer inflations have values close to zero. Also, ^{Pujol and Griffiths (1998)} report inelastic coefficients (0.06) from foreign inflation to local producer inflation. ^{Gil Díaz and Ramos Tercero (1992)} mention that the exchange rate elasticity with respect to key inflationary prices was 0.921 for the 19761982 period in Mexico. For these authors, this result seems to indicate that the exchange rate was used to stabilize the general price level. Burtein et al. (2005) report similar results for the U.S. economy.
The bilateral nominal exchange rate is negative in the longterm equation (6) and positive in the shortterm equation (8), with respect to consumer inflation. This is in so far as these estimators are close to zero. During the period 20072016, associated with the Great Recession, the regulation of the bilateral nominal exchange rate with two lags, contribute in the short term to a minimal increase in consumer inflation.
In the long term, the producer inflation estimators with respect to consumer inflation are 1.05 and 1.07 for each period, respectively. These values imply almost flexible prices for both periods^{14}^{,}^{15}. In the short term, the producer price inflation estimator with respect to consumer inflation are 0.80 and 0.25 for each period, respectively. Thus, producer prices are positively transferred into consumer prices, although not completely.
The longterm equation (5) and (6) do not need any lag. In the shortterm equation (7) and (8) required lags: equation (7) for wages (3 lags for the period 20072016) and the bilateral exchange rate (1 lag for the period 19942013); equation (8) for wages (3 lags for the period 20072016) and the bilateral exchange rate (2 lags for the periods 19942003 and 20072016). Besides, equations (7) and (8) include the error correction terms with a statutory one lag^{16}.
The results reported on table 4 indicates that the error correction terms
data id  period  integration order  significance  PP, ADF critical values  PP Adj. tstat.  ADFtstat.  option 


1994200  I(0)  1% level  3.492.882.58  7.337.407.36  2.981.822.99  ABC 

19942003**  I(0)  1% level  3.49 2.88 2.58  7.10 7.26 7.13  3.42 3.65 3.44  A B C 

20072016**  I(0)  1% level  3.48 2.88 2.58  5.12 6.19 5.15  2.61 2.63 2.62  A B C 

20072016*  I(0)  1% level  3.48 2.88 2.58  3.48 2.88 2.58  2.80 2.79 2.82  A B C 
Note: Bandwidth NeweyWest automatic selection using Bartlett kernel. *Bandwidth NeweyWest 12 userspecified using Bartlett kernel; ** user specified lag length 2 (fixed). Included in test equation: A constant; B constant, linear trend; C none. Mackinnon (1996) onesided pvalues for rejecting the null hypothesis of having a unit root. All test results are reported at the 99% of statistical significance. Source: residuals from the long term estimated equations for the periods 19942003 and 20072016, using EViews 9.0.
The error term unit root tests indicate that
19942013  

Null hypothesis  n  FStatistic  Probability 
Longterm  

108  7.92760  0.0006 

8.71174  0.0003  

108  67.0974  0.0000 

0.34412  0.7097  

108  7.92760  0.0006 

8.71174  0.0003  

108  1.13419  0.3257 

2.86708  0.0614  

108  32.4225  0.0000 

0.27402  0.7609  
Shortterm  

107  7.61008  0.0008 

0.28056  0.7559  

106  4.23847  0.0171 

1.93156  0.1502  

107  7.39791  0.0010 

0.29157  0.7477  

107  4.80739  0.0101 

3.80633  0.0255  

105  16.5496  0.0000 

34.8010  0.0000  
20072016  
Null hypothesis  n  FStatistic  Probability 
Longterm  

112  2.67438  0.0000 

27.6836  0.0000  

112  19.6372  0.0000 

2.34696  0.1006  

112  0.45398  0.0000 

48.3725  0.0003  
ipp does not Granger cause 
112  2.78217  0.0664 

0.94572  0.3916  

112  4.79279  0.0102 

1.97305  0.1441  
Shortterm  

107  7.61008  0.0008 

0.28056  0.7559  

106  4.23847  0.0171 

1.93156  0.1502  

107  7.39791  0.0010 

0.29157  0.7477  

107  4.80739  0.0101 

3.80633  0.0255  

105  16.5496  0.0000 

34.8010  0.0000 
Note: the number of lags is two, n represents the number of observations.
Source: own estimation using EViews 9.0.
Regarding table 5 results, for the period 19942013 it cannot be rejected that wages do not Granger cause the producer and consumer price indexes, with short term probabilities of 0.0008 and 0.0010, respectively. Similar results are observed in the short term for the period 20072016, with respect to wages and producer and consumer price indexes: 0.0008 and 0.0010, respectively. In the short term, it cannot be rejected that the bilateral exchange rate does not Granger cause the producer price index, with probability of 0.0171 for both periods; likewise for the consumer price index: 0.0000 for both periods.
In the short term, it cannot be rejected that producer price index does not Granger cause the consumer price index, with probabilities of 0.0101 for both periods. In the long term, it cannot be rejected that the bilateral exchange rate does not Granger cause the producer and consumer price index with probabilities close to 0.0000 for both periods. In the short term, it appears that Granger causality runs oneway from wages to price indexes and not the other way. Likewise for the bilateral exchange rate and the producer and consumer price indexes; and for the producer price index and the consumer price index. In the long term, it appears that Granger causality runs oneway from the bilateral exchange rate to the producer and consumer price indexes. The pairwise Granger causality test results seems to sustain those equations (5), (6), (7), and (8) are well specified. Granger tests have not provided empirical evidence of a strong statistical causality from wage growth to inflation. Similar results have been reported by ^{Hess and Schweitzer (2000)}; ^{Hogan (1998)}; ^{Rissman (1995)}; ^{Clark (1997)} and ^{Mehra (1993)} in the United States context.
Conclusions
An error correction model in the long and short term was proposed for Mexican manufacturing, for two sets of periods: 19942003 and 20072016. Wages have an almost nil effect in manufacturing producer and consumer prices, in the long and short terms during the periods under study. The pairwise Granger causality tests have not provided empirical evidence of a strong statistical causality from wage growth to inflation tests, and signal that the error correction equations (5), (6), (7) and (8) are well specified. Together, these results are at odds with the markup price function traditional theoretical tenets. This body predicates upon wage increases as a source of inflation.
It appears that there are sticky import prices in the long and short terms. In the short term, the bilateral nominal exchange rate estimators respect to producer and consumer inflation are close to zero. These inflations seem unaffected by bilateral nominal exchange rate regulations. The bilateral nominal exchange rate changes from negative (equation 6) to positive (equation 8) signs, with respect to consumer inflation. This last point is a matter for further analysis.
The manufacturing producer inflation estimators, with respect to consumer prices are almost elastic in the long term. They exhibit almost unitary values in the long term for both periods. Hence, producer price index increases are almost totally transferred to consumer prices. These results suggest that there are flexible prices from the manufacturing producer to the consumer. However, in the shortterm producer prices are not transferred with a unitary elasticity into consumer prices.
The long and short terms estimation results provide insight of the presence of sticky prices regarding wages. These results point out to a relatively weak role of wages in consumer and producer inflations. Thus, it seems statistically fair to infer those wages are not inflationary in Mexican manufacturing, for the periods under analysis. In this case, policies targeting wage inflation controls seem inefficient in controlling producer and consumer price inflations. As a result, policies that seek inflation control could leave wage inflation controls aside.