Unemployment in Mexico

The importance of the unemployment rate in Mexico turns out to be a very important indicator for the evaluation of the economic performance of a country, thus the interest given to the analysis of the role that it plays in the Mexican economy. According to the results of the Encuesta Nacional de Empleo (ENOE) (National Employment Survey), at the closure of 2014, 59.86% (participation rate) of the population in working age (not of 14 years but above 15 years, given the recent constitutional reform that added a year to the minimum working age) was economically active (EAP, people employed or looking for employment), a lower percentage than the one of the previous year (61.08%). 96.24% of the EAP was identified as Working population (WP), which means that the unemployment rate (UR) was of 3.76% in December (against the 4.53% in November, the 4.27% a year before and the 4.20% expected), decreasing for the fifth month in a row and situating itself at its lowest level in at least two years. Thus, the average UR of 2014 was of 4.83%, lower to the 4.91% of 2013.

The good result of the unemployment rate in December of 2014 coincides with the favorable end in matters of formal employment generation, as the number of insured workers in the IMSS (despite its usual setback of the last month of each year) was lower than the one of 2013, while its growth rate improved from 4.2% to 4.3%, being the most dynamic since January 2013. This reflected an improvement in the rhythm of economic activity in the last quarter of 2014 that, should it extend to 2015, should contribute to keeping a labor dynamism that is at least similar to that at the closure of 2014.

Fig. 1 shows the evolution of the unemployment rate from 1999 to 2014, in which the last 14 years presents an upward trend and a break with regard to the tendency after the peak of the unemployment rate (6.15) reached in 2009, this as a consequence of the global liquidity crisis. The slight decrease of rates in the last five years is due to the scarce economic activity in Mexico, with annual economic growths inferior to 3% after the last world crisis and to the labor reform implemented in the current presidential administration. This coincides with the favorable year closure with regard to the creation of formal employment and to an improvement in the economic activity rhythm at the end of 2014. Should this behavior continue in 2015, it would contribute to keeping a labor dynamism that is at least similar to the closure of 2014.

Performance of the gross capital formation in Mexico

In all economic investigations related to the economic growth of a country, the GCF investment is a determining factor in the representation of the engine that boosts an economy forward. From the beginning of the 1980s, investment in Mexico, as with the rest of the world, has been defined with regard to the conditions that the financial globalization imposes. However, Mexico has not managed to establish a favorable dynamism regarding the accumulation of capital that allows experiencing a vigorous growth rhythm. This situation has been analyzed by ^{Avendaño and Perrotini (2015)}, who argue that the growth of the GCF has been insufficient to absorb the labor force of the economy.

In Mexico, from the 2000 to 2008, the investment component of the GCF presented a stage of growth that was stalled by the effects of the global liquidity crisis, which caused a growth rate of 9.75% between 2008 and 2009. While since 2010 to the closure of 2014, the GCF has only had a quarterly mean growth of only 2.81%, demonstrating the low levels of dynamism and the lack of economic growth in Mexico.

The GCF variable that is comprised in the record on the expenses made in national and imported machinery and equipment, as well as those resources that were used to develop residential and non-residential constructions, reported a growth of 5.7% at an annual rate reported in 2013 of −4.8%, with this figure being positive since its peak in May 2014.

In the aggregate, the balance that the GCF presents in September has a moderately positive slant, particularly due to the peak regarding the decreases recorded since 2012; within this comparison, the component of machinery and equipment that evolves with greater dynamism than construction, stands out; in spite of this, this impulse is still not consistent enough with the rhythm of industrial production, forcefully linking us to the decreasing vigor in the demand of the internal market. On the other hand, even if the investment in construction has shown a boost in recent years according to its annual rate (particularly in residential construction), this has not had the sufficient strength to revert the negative figures in the annual variation accumulated for more than two years.

Exports in Mexico and their compositions

At the closure of 2014, the commercial balance in Mexico recorded a surplus of 254 million dollars (md), same that was lesser to the one in the previous year (1626 md) and contrary to November's deficit (−1076 md). This result originated from a vigorous annual acceleration of exports, from 2.1% to 6.4%, same as with imports, from 6.5% to 11.2%.

In the composition of last year's exports, it was emphasized that the oil companies notoriously accented their annual deterioration rate, from −13.2% in 2013 to −43.7% in 2014, while the non-petroleum companies significantly improved their advance, from 4.0% to 14.3%, with manufacturing companies going from 4.0% to 15.8% in 2013 and 2014 respectively.

Regarding the destination of the manufacturing sector, the exports that go to the USA accelerated their growth from 6.3% to 16.2% annually and toward the rest of the world from −5.2% to 6.2%. However, the commercial balance of all of 2014 was a deficit of 2441 million dollars, higher than the one observed in 2013, when it was of 1184 million dollars, with external sales reporting an accumulated increase of 4.6% and the foreign purchases of 4.9% (in light of increases of 2.5% and 2.8%, respectively, a year before).

If the United States economy remains this solid and the recovery rhythm of the economic activity and the consumption levels in Mexico improves, the export and import dynamism will continue to improve. Although, it should not be overlooked that as long as the prices of oil do not recover and the structural reform of the energy sector is not implemented, creating more investments in the sector, this will continue to be reflected in the low levels of oil exports.

Importance of the monetary aggregate (M1) as financial stabilizer in Mexico

In Mexico, the monetary policy has as its main objective to maintain inflation stable. However, said policy has effects on unemployment. The monetary policies link these variables, and therefore require a prediction of the effect that a change in these would have and the quantity of money or interest rate on unemployment in order to establish a more accurate monetary policy.

For the closure of 2014, the monetary policy showed the need to strengthen the macroeconomic framework in the face of a highly uncertain and complicated global financial environment. In the USA, the economy continued to consolidate its recovery with the strengthening of the global market, and the Federal Reserve of the USA withdrew its normalization plans in its monetary stance. Whereas in the case of Mexico, the economic activity showed a moderate recovery, with the external sector being the main trigger of the growth, combined with a greater dynamism in private investment, however, with uncertainty of lesser levels of growth than those predicted.

Macroeconomic context in Mexico

Generally, the behavior of the prices of petroleum and explained in the degree of exports, combined with the management of possible increases in interest rates in the USA at the closure of 2014, reflected a less expansive macroeconomic stance. In Mexico, the total employment is still weak at the closure of 2014 in spite of the expansion of formal employment, and the real total payroll continues to decrease, which causes an obstruction in consumption. Lower petroleum prices could reflect the reduction of profitability of the projects that would result from the energy reform; and with this, a decrease on the effects of the daily economic activity. There is the risk that other structural reforms, such as that of competition, do not have the expected result. In addition to the aforementioned, the broad deficit of the non-petroleum commercial balance could imply a risk of a financing shock in the economy that would impact a rise in inflation.

The macroeconomic environment that the Mexican economy faced at the closure of 2014 generated pressures on the real exchange rate and the interest rates, and thus in this context the fiscal policy must be an anchor in order to be able to absorb said pressures in an orderly fashion. It is urgent to stabilize the growth of the financial requirements of the public sector, which have gone from 26% of the GDP in 2006 to 42% of the GDP at the closure of 2014. Therefore, the monetary policy always plays a rather important role in facing the external environment, for the anchoring of the expectations of inflation and in order to prevent a disorderly displacement in the yield curve.

The increases in the prices of high-calorie foodstuff that came about as consequence of the new tax implemented in 2013. The inflation at the closure of 2014 was found to be above 4% in good measure by transitory effects such as these.

For 2015, many of these effects will disappear, and there will be other factors that ought to help for a quick decline of inflation such as, for example, the manner in which the elimination of fees in telecommunications is measured, such is the case of the long-distance fees. These types of effects are also transitory, and thus, it should not be thought that inflation is already fully complying with the goal. There are other factors whose possible evolution is still unknown, but that could have a rather significant effect on inflation, such as a significant increase in the minimum wage or the permanence of the high levels in the exchange rate. Considering that the Federal Reserve of the USA appears to be in line with a first increase of its interest rates toward the middle of the year, and in the face of the high probability of it becoming a reality, during the first half of the year, an increase in the minimum wage above the expected inflation and of the expected earnings in productivity; we can conclude that it would be during the middle of 2015 when Banxico begins to raise its reference interest rate.

Stationarity tests of the endogenous variables

Based on the results obtained and seen in the multiple balances of unemployment, we can affirm that the reforms meant to reduce the extra labor benefits could constitute important positive shocks if implemented in the employment recovery phase, thus reducing the unemployment rates (^{Aranda, 2003}). However, when the reforms are implemented in periods of growing unemployment, these cannot have the desired effect due to the fact that the potential beneficial effect of the reform is offset by a negative shock (Monetary Offer and Exports) that affects the economy.

Within the temporal evolution analysis of the variables used, it can be observed in Figs. 1-4, that the behavior of the series empirically shows a lack of stationarity based on the reflection of growths and tendencies.

Fig. 1 Quarterly unemployment rate 2000-2014. 

Fig. 2 Quarterly gross capital formation 1999-2014 (million pesos). 

Fig. 3 Quarterly exports 1999-2014 (millions of pesos). 

Fig. 4 Monetary aggregate M1 quarterly 1999-2014 (millions of pesos). 

With the purpose of modeling the behavior in time by means of autoregressive techniques, it was considered to transform said independent variables (FMK, M1, and EXP) into logarithmic variables, homologizing the characteristics of econometric analysis with the Unemployment variable. An analysis carried out in order to corroborate the existence of stationarity, was the validation of the correlograms of each of the series (Table 3).

Through a difference, that is, integration of the first order I(1), it allows the identification of the linear combination of stationarity. Its representation is found with a “D” in each variable: DDES, DEX, DGCF, and DM1. In order to explain the evolution of the series in the course of time and predict its future values, it was required to validate the transformation of non-stationary variables to stationary variables, i.e., proof the effectiveness of the elimination of tendency and heteroscedasticity through the differentiation 1 (Table 4).

Only one lag was used and variables in logarithm, which represents a generalized consideration of variables per quarter. This allows the validation of the autocorrelation of the residuals and thus the necessary parsimony, in the sense of not including an excessive number of lags. Therefore, it is thought that the series considered would be integrated of the first order I(1) and the first differences would be stationary.

Causality of macroeconomic variables with unemployment in Mexico

In order to describe and infer in the causal dynamic between unemployment and the endogenous macroeconomic variables mentioned, based on the autoregressive vector models, Table 5 can be validated.

In this way, it is detected that it complies with the modeling principles required in this investigation; first the independent variables (endogenous) cause the unemployment variable, in addition to avoiding problems of reciprocal correspondence.

Long-term co-integration test of endogenous variables

Given a group of non-stationary endogenous variables, it was of interest to determine if the series are co-integrable or not with unemployment, and if they were, identify the co-integration relations in the long-term balance. The methodology used in this type of analysis was the Johansen method, considering a VAR with order p; y _t = A ₁ y _t−1 + ⋯ + A _p y _t−p + Bx _t + E _t , where y _t is a k-vector of the non-stationary contemporary endogenous variables mentioned (DES, DEX, DGCF, and DM1) I(1), y _t−1 vector of aforementioned endogenous variables, lagged one period, x _t is a d-vector of deterministic variables, A _i matrices of coefficients of regression to be estimated for i = 1,2,…,p and E _t is a vector of innovations, which are assumed as not serially correlated.

Therefore, in this case the Vector Error Correction Model (VECM) cannot be used, thus opting for analyzing a UVAR system (Table 6).

The unrestricted VAR model

The model implemented for the Mexican case takes the model proposed by ^{Maurer and Doris (1994)} as reference, which describes the changes in some macroeconomic variables in order to demonstrate the existence of hysteresis. Thus, the model proposed is expressed as follows:

where α _t : unemployment in period t; λ: the fraction of unemployment for the period t − 1; Z _t : some endogenous macroeconomic variables in time t and A: weight coefficient.

It is important to mention that in the model, due to the existence of memory, the effects of a policy reflected by variable Z weighted by coefficient a transfer to unemployment time t or present.

In hysteresis, unemployment in the current period t is exactly equal to period t − 1, though it ought to be clarified in the case that there are no other factors that exercise influence on it. The general definition of hysteresis refers to the persistence or inertia, so that for unemployment during a period it shall be a fraction λ of the previous unemployment; these values are between 0 and 1 and indicate a strong or weak persistence. A λ value greater than 1 would make no sense as it indicates an explosive amplification of unemployment; a λ value equal to zero indicates the absence of an intertemporal process of unemployment.

The unrestricted autoregressive vector, UVAR, is obtained given a number of delays, with the representation I(1) obtained in Table 1. The qualifier “unrestricted” reflects the fact that the UVAR model incorporates a minimum of restrictions necessary to be operational.

The UVAR model has been highly used in the applications of the VAR methodology. On the one hand, due to its broad generality as an instrument to represent stochastic processes and, on the other, its easy estimation through methods with adequate statistic properties, such as the method of ordinary least squares (OLS). This method possesses a normal asymptotic distribution, being the most efficient unbiased linear estimator. Thus, in the UVAR framework, we look for unemployment to have stochastic and non-deterministic regressors as it occurs with the simple linear regression, in addition to the fact that the vector of disturbances is present in a succession of random independent vectors, without autocorrelation between the current value of disturbance and the regressors of the model.

Based on the analyses of ^{Maurer and Doris (1994)}, considering the analyses of the temporal series in previous sections, an equation that explains the effect of hysteresis in the labor market in Mexico is suggested.

Through a linear model of the five variables determined in Eq. (2), the behavior of Unemployment in Mexico can be explained by its very own lagged values in a quarter, determined with the unit root tests and with the causality tests. Thus, the UVAR model can predict the interrelated system of the series of time in order to measure the dynamic impact with the dependent variable with random disturbances.

Econometric diagnostic of UVAR

The optimal lag for the modeling was determined through the Schwartz Criteria, which indicates that with a minimum value of −9.51, a lag is sufficient (Table 7).

Table 8 shows the results of the econometric estimation of the model.

The results of the estimation of the model show that all the variables are statistically significant. Furthermore, the model has a goodness of fit of 85% and the ^{Durbin-Watson (1971)} statistic shows the absence of autocorrelation. The value obtained for unemployment is found in a range of 0 > 78 < 1, thus there is persistence considering these variables. The estimations carried out by ^{López (1993)} base their analysis on a random function based on the Weibull distribution¹⁰ and the insertion time in the labor market of an unemployed person, the time scheme goes from one to twelve months, and it also shows that there is a relation between the probability that an unemployed person has of entering into the market with the market and the hysteresis coefficient.

Autocorrelation

The ^{Breusch (1978)} and ^{Godfrey (1978)} test was carried out in order to detect the presence of serial dependence, as if that is the case, the conclusions are incorrect (Table 9).

The correlations between combinations of endogenous and lagged variables of the model did not show problems of autocorrelation. If the aforementioned is corrected, then the VAR model determined for the estimation of Unemployment must not have any residual autocorrelation.

In Table 10, we can observe that the p -value is equal to zero, indicating that there is no Serial Correlation and thus the terms of error within the model of unemployment are consistent.

Normality

Though a statistic process to determine if the data could adjust to a normal standard distribution, the residuals of the UVAR model of Unemployment showed a distribution with a median of zero and a constant variance. Nevertheless, ^{Fernandez-Corugedo, Price, and Blake (2003)} argues that it is more important that the UVAR complies with the no autocorrelation test of errors than with the multivariate normality. However, through the Choleskey (^{Lutkepohl, 2005}) text, the normality of the proposed Unemployment model was validated (Table 11).

Graphically, the residual series of the unemployment model shows a normal distribution, with a probability of the ^{Jarque-Bera (1987)} test of 0.3991, above the 5% of the significance level (Fig. 5).

Fig. 5 Residual normality test VAR. 

Homoscedasticity

Under the existence of normality in the series of residuals of the unemployment model (median zero and constant variance), we looked to satisfy the assumption that all the terms of error have the same variance, i.e., the errors are homoscedastic (^{Achen & Shively, 1995}).

The proposed unemployment model shows Homoscedasticity in the errors in joint probability (Table 12).

Table 12: VAR heteroscedasticity test. 

Source: Own elaboration with the use of the econometric analysis package of Eviews8.

Impulse-response functions

The VAR methodology's objective is to isolate primitive sources of economic variability, created by diverse economic, political and social natures, from the public or private sectors, or from the exterior sector of the economy. Therefore, with the VAR modeling there tends to be an interest in the dynamic effects of said primitive disturbances in the evolution of the Unemployment variable that characterizes this study.

In the estimations, the option of generalized impulses posed by ^{Pesaran and Shin (1998)} is employed for the estimation of the impulse-response functions. In light of this, the vector function of response to impulse quantifies the effect on the variables of the system, throughout a time horizon, of an isolated impulse equal to the unit in each of the “n” disturbances of the model.

The impulse-response functions help to better visualize the relations between the macroeconomically used variables (Unemployment, Gross Capital Formation, Exports and Monetary Offer). Such functions illustrate the effect that a random shock in one of the variables has on the rest of the variables of the system (Figs. 6-9).

Fig. 6 Impulse-response function of the unemployment level against a shock in a standard deviation of the same unemployment. 

Fig. 7 Impulse-response function of the unemployment level against a shock in a standard deviation of exports. 

Fig. 8 Impulse-response function of the unemployment level against a shock in a standard deviation of the gross capital formation. 

Fig. 9 Impulse-response function of the unemployment level against a shock in a standard deviation of the monetary attachment M1. 

In the case of the VAR(p) models, that use stationary variables, from which the impulse-response functions of the system are derived. The VEC models, due to being comprised by non-stationary variables, are not represented in this investigation. It is worth remembering that in stationary processes the responses of the variables in the face of random shocks must fall over time, so that they tend toward zero when t → ∞.

Given that the interest of this paper falls on the variable of the percentage of unemployed, the Figures of response for the DES variable in the face of an impulse (random shock) on the DES, GCF, EX, and M1 variables are shown. Orthogonal response impulses will be used built from an innovation of a standard deviation in the transformed method, and the horizon utilized was of 20 periods. That is, the responses of the DES variable were shown in a horizon of five years subsequent to the shock of each independent variable.

As was to be expected, the strongest response in the percentage of unemployed was obtained for a random shock in the GCF investment variable, i.e., if there is a negative shock in investment, its effect is a direct rise on unemployment, which will then have its effect for up to a year, reaching a balance after two and a half years. On the other hand, a labor offer shock has the effect of reducing the percentage of unemployment for up to a year and a half after the initial impulse.

In the sense of an open economy, a shock in exports reduces the percentage of unemployment up to a year following the initial shock; afterwards, the effect turns out to be greater than the initial point, when there is once more an increase in the percentage of unemployment as consequence of stationary behavior since 2010, subsequent to the global liquidity financial crisis. Although the control exerted on the monetary offer has the purpose of controlling the economic effects caused by inflation, this variable shows a direct relation, i.e., in light of a shock in the M1 monetary aggregate; the effect on the percentage of unemployment always results positive throughout the subsequent time horizon. That is, the shock in the M1 causes an increase in unemployment, given that the disposition of liquidity causes a greater demand of goods and services, which is reflected in the productive sector through the increase in its production costs, therefore, said sector is more productive with an increase in gross capital formation and possible reductions in the variable costs of direct labor.

Finally, this investigation gives rise to the identification of possible theoretical non-compliances in future investigations, such as the case of the Phillips Curve law, which in some periods is not applicable as indicated by the methodological origin.