Why Mexico's regional income convergence broke down

Journal of Development Economics 77 (2005) 257 – 275 www.elsevier.com/locate/econbase

Why Mexico’s regional income convergence broke down Daniel Chiquiar* Direccio´n General de Investigacio´n Econo´mica, Banco de Me´xico. Av. 5 de Mayo 18-1er. Piso. Col. Centro, 06059 Mexico, DF, Mexico Received 10 October 2003; accepted 1 March 2004

Abstract According to previous research, Mexico’s trade reforms led to a divergent pattern in regional percapita output levels. This research did not fully include Mexico’s regional growth performance after 1994, when NAFTA started operating. In this paper, I extend the sample to include Mexico’s regional growth patterns after this treaty was enacted and I explore what factors may account for this result. The findings suggest that the divergent pattern observed after 1985 was not reversed with NAFTA. The results also suggest that the winners from the reforms were those states initially endowed with, or able to attract, higher levels of human and physical capital and better infrastructure. D 2004 Elsevier B.V. All rights reserved. JEL classification: O4; R1 Keywords: Trade liberalization; Regional convergence; NAFTA

1. Introduction According to previous research, the effects of Mexico’s trade liberalization, which started in the mid-eighties when the country signed on to the General Agreement of Tariffs and Trade (GATT), were not uniform across its regions. The initially richer northern states that have a border with the U.S. seem to have reaped most of the benefits from the reforms, while the central and southern states hardly exhibited an improvement in their growth * Tel.: +52 37 27 51; fax: +52 37 26 85. E-mail address: [email protected]. 0304-3878/$ - see front matter D 2004 Elsevier B.V. All rights reserved. doi:10.1016/jdeveco.2004.03.009

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performance. As a consequence, the convergent pattern in regional per-capita output levels that was observed before the reforms apparently broke down after 1985. These studies, however, were mostly based on samples including only a short period of time after the reforms and, in particular, did not fully include Mexico’s regional growth performance after the North American Free Trade Agreement (NAFTA) started operating in 1994. Moreover, most previous research has not explored in detail the forces that may have induced the loss of convergence across Mexico’s regions. In this paper, I extend the sample used by previous authors to include the post-NAFTA experience and explore what kind of factors may account for the loss of convergence in Mexico’s regional per-capita GDP. The empirical evidence I present supports the hypothesis that, after 1985, b-convergence across Mexican states’ per-capita outputs was lost, even if we control for differences in steady state per-capita output levels. Moreover, according to the results, the divergent pattern observed after that year was not reversed with the enactment of NAFTA. The findings also suggest that Mexico’s reforms induced a structural change in its growth patterns, as new sources of growth related to trade and investment flows became available. Not many states, however, were prepared to take advantage of these new sources of growth. In particular, the winners from trade liberalization were apparently states initially endowed with, or able to attract, higher levels of human and physical capital and better infrastructure. This was especially true for the border region, which benefited additionally from its proximity to the U.S. market. In contrast, southern states, whose labor force is more concentrated in traditional agriculture and have the greatest deficiencies in human capital and basic infrastructure, seem to be the losers from trade liberalization. The paper proceeds as follows. In the first section I summarize the existing literature concerning the regional effects of the reforms. Section 3 provides a general description of the evolution of per-capita output in Mexico’s regions from 1970 to 2001. In Section 4, I study the existence of absolute and of conditional convergence across Mexican states. Finally, Section 5 summarizes the main conclusions.

2. Previous research on the regional response to trade liberalization The literature has identified several mechanisms through which the trade reforms had heterogeneous effects across Mexico’s regions. Among these, the most important seem to be the following. First, trade liberalization altered the optimal location choice of manufacturing firms, promoting a break-up of Mexico City’s manufacturing belt and a movement of economic activity towards the border with the U.S. Indeed, after Mexico opened up to trade in 1985, a dramatic reduction in Mexico City’s share of manufacturing employment was observed. At the same time, the states that have a border with the U.S. exhibited an increasing trend in their share of overall manufacturing employment.1 This behavior may be accounted for with simple economic geography models. For instance, Krugman and Livas Elizondo 1 From 1980 to 1998, the share of total manufacturing employment in Mexico City decreased from around 45% to 23%. In the same period, the share corresponding to border states increased from 21% to 34% (data from Hanson, 1998a, and Mexico’s Industrial Censuses for 1998, INEGI, 1998).

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(1996) argue that the import substitution policy applied from the mid-forties to the mideighties was a determinant factor leading to the concentration of manufacturing employment in Mexico City. In contrast, once the economy opened up, firms started selling a larger fraction of their output to foreigners and purchasing inputs from abroad. Thus, the forward and backward linkages that supported the agglomeration in Mexico City became weaker, leading firms to move away from it and to locate close to the border with U.S., in order to economize on transport costs (Hanson, 1997, 1998a,b). Second, a strong increase in the relative wage of skilled workers was observed after Mexico’s trade liberalization. Some evidence suggests that this increase is linked with the activities of export-oriented and foreign-owned firms (Harrison and Hanson, 1999; Aitken et al., 1996). As a consequence, the increase in the skill premium was more apparent in the border region, where this kind of firms is mostly concentrated. This evidence has led some authors to link the increase in the skilled–unskilled wage gap in Mexico to trade reform (Feenstra and Hanson, 1997; Markusen and Zahniser, 1997).2 Finally, trade liberalization and, in particular, the reciprocal reduction in trade barriers implied by NAFTA, tended to benefit northern agricultural activities, which are characterized by the use of modern technologies and irrigated land and are concentrated in fruits and vegetables for which Mexico holds a comparative advantage. In contrast, southern peasants (which are concentrated in subsistence agriculture based on traditional techniques and rain-fed land) have been strongly hit by the elimination of protection on the products they traditionally concentrate on (Brown et al., 1992; Levy and Van Wijnbergen, 1995; Veeman et al., 2002). 3. A regional perspective of Mexico’s recent growth performance3 Table 1 provides a summary of the recent evolution of per-capita output across Mexican regions. There are several features that can be observed from the data. First, there was no 2 However, the behavior of relative wages in Mexico after 1985 seems to be inconsistent with a Heckscher– Ohlin framework. Thus, some authors have argued that skill-biased technological change, and not trade, may be the main driving force behind the increase in the skill premium (Cragg and Epelbaum, 1996; Robertson, 2000b; Alvarez and Robertson, 2001). Others have linked rising wage inequality in Mexico, at least in part, to high emigration rates among relatively skilled workers (Chiquiar and Hanson, 2002; Mishra, 2003). It is worthwhile to mention that most authors have analyzed the behavior of the wage gap using evidence corresponding only to the first stage of the reforms, when Mexico opened up to trade unilaterally. Robertson (2000a) argues that it was only after the enactment of NAFTA, when Mexico became substantially more integrated with skill-abundant countries. He provides evidence that the skill premium started falling after NAFTA. Chiquiar (2003) provides further evidence that, after this treaty was enacted, the skill premium decreased in the border region, as compared with the rest of the country. Similarly, using a bmandated wage equationsQ approach, Esquivel and Rodrı´guez-Lo´pez (2003) find that technological change, and not trade, seems to be the main factor explaining the rise in the wage gap in Mexico. The evidence, therefore, has gradually become more supportive of the Heckscher–Ohlin framework. This suggests that the rise in the skill premium in Mexico may have been a consequence of factors possibly not directly related to trade liberalization. 3 Throughout the following sections of the paper, I exclude the states of Campeche and Tabasco from the analysis. A very large, but also very volatile share of these states’ GDP, is generated from the exploitation of oil reserves by PEMEX, the government-owned oil firm. As a consequence, their per-capita output figures are not representative of their welfare levels and their growth rates are strongly affected by the activity of this firm.

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Table 1 Per-capita GDP by state

National Border Baja California Coahuila Chihuahua Nuevo Leo´n Sonora Tamaulipas Northern central Aguascalientes Baja California Sur Durango Nayarit San Luis Potosı´ Sinaloa Zacatecas Southern central Colima Guanajuato Hidalgo Jalisco Michoaca´n Morelos Puebla Quere´taro Tlaxcala Veracruz Mexico City Distrito Federal Me´xico South Chiapas Guerrero Oaxaca Quintana Roo Yucata´n

Per capita GDP (national average=100.0)

Annual per capita growth (percentage)

1970

1970–1985 1985–2001

100.00 128.70 144.98 120.07 101.17 166.48 138.44 104.74 72.55 79.46 138.68 71.52 75.85 58.39 93.58 51.44 74.86 85.56 71.22 53.86 103.78 52.44 84.11 61.98 79.06 45.63 81.24 162.13 192.37 107.90 48.71 49.23 51.67 35.24 97.98 71.50

1985

100.00 125.30 129.85 120.32 102.24 164.64 119.50 102.82 79.04 85.59 117.73 90.17 79.56 70.18 84.61 59.42 78.77 107.88 70.73 69.33 106.45 55.72 86.08 67.71 109.10 75.66 75.59 143.90 189.14 99.13 62.65 69.01 56.95 50.93 117.55 70.94

1993

100.00 129.28 126.63 120.55 128.58 165.81 114.79 100.67 79.52 105.42 132.27 80.72 66.15 72.55 86.70 55.58 72.86 103.29 69.01 64.93 100.01 54.39 96.69 63.60 104.67 52.96 60.74 154.42 248.09 82.42 60.04 45.30 58.24 46.05 183.06 76.63

2001

100.00 135.73 124.19 130.07 138.73 173.74 123.96 104.28 80.77 122.61 127.15 85.56 61.96 73.11 81.03 56.58 73.10 95.32 68.74 60.47 99.28 56.88 91.48 65.73 118.16 56.13 58.04 148.49 255.24 79.71 57.15 42.63 52.13 42.48 151.21 80.21

1.82 1.64 1.08 1.84 1.89 1.75 0.83 1.70 2.41 2.33 0.72 3.41 2.15 3.08 1.14 2.81 2.17 3.41 1.78 3.55 2.00 2.24 1.98 2.42 4.03 5.31 1.33 1.02 1.71 1.25 3.55 4.14 2.49 4.35 3.07 1.77

Total

1985–1993 1993–2001

1.13 1.64 0.85 1.62 3.08 1.47 1.36 1.22 1.27 3.43 1.62 0.80
0.44 1.39 0.86 0.82 0.66 0.35 0.95 0.27 0.69 1.26 1.51 0.94 1.63
0.74
0.53 1.33 3.04
0.24 0.55
1.87 0.57
0.01 2.73 1.91

0.78 1.18 0.47 0.81 3.71 0.87 0.28 0.52 0.86 3.44 2.26
0.60
1.52 1.20 1.09
0.05
0.19 0.24 0.47
0.04 0.00 0.48 2.26 0.00 0.26
3.61
1.93 1.68 4.26
1.52 0.25
4.38 1.07
0.48 6.52 1.76

1.48 2.09 1.23 2.44 2.44 2.07 2.45 1.92 1.67 3.41 0.98 2.22 0.65 1.57 0.62 1.70 1.52 0.46 1.43 0.58 1.38 2.04 0.78 1.89 3.02 2.21 0.90 0.98 1.84 1.05 0.85 0.71 0.08 0.46
0.92 2.05

Source: INEGI. Campeche and Tabasco are excluded from the sample.

important mobility from 1970 to 2001 in the relative position that the states had in terms of their per-capita GDP ranking. In particular, most southern and central states, which tended to be the poorest in 1970, are still the poorest states as of 2001. Second, the periods from 1970 to 1985 and from 1985 to 2001 are qualitatively different in an important way. From 1970 to 1985, the states that had per-capita outputs below the average grew relatively faster than the rest so that, in general, they were gradually catching up with the rest of the country. In effect, the highest rates of growth during this period were observed in most

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261

central states surrounding Mexico City (but not in the city itself) and, especially, in the southern part of the country. In contrast, after 1985 this trend broke down: the poorest regions tended to exhibit smaller growth rates than richer states from 1985 to 2001. The scatter plots in Fig. 1 tend to confirm this view. Restricting the data to the years after NAFTA was enacted yields additional insights. As can be observed in Table 1, from 1993 to 2001 growth seemed to be negatively correlated with distance to the U.S. In particular, the highest growth rates were attained by the border states, while the smallest rates of per-capita growth were observed in Mexico City and, especially, in the southern region. The scatter plot in Fig. 1 corresponding to this period suggests that, controlling for an outlier (the tourism-oriented state of Quintana Roo, which exhibited an extremely small growth given its high per-capita output level), the divergent pattern in per-capita GDP remained unaltered during the period 1993–2001. Thus, apparently NAFTA did not break down the divergent pattern in regional per-capita output observed after the initial stage of the reforms. The growth patterns described above are consistent with the mechanisms discussed in the previous section and, especially, with Hanson (1996, 1998b). The presence of agglomeration economies may have still provided incentives for firms to locate close to Annual Growth 1985-2001 vs. Initial GDP .04

.05

.03

Growth 1985-2001

Growth 1970-1985

Annual Growth 1970-1985 vs.Initial GDP .06

.04 .03 .02

.01 .00 -.01

.01 .00 8.0

.02

8.4

8.8

9.2

9.6

10.0

-.02 8.4

8.8

Log GDP 1970

9.2

9.6

10.0

10.4

Log GDP 1985 Annual Growth 1993-2001 vs. Initial GDP

.04

Growth 1993-2001

.03

.02

.01

.00 Quintana Roo

-.01 8.5

9.0

9.5

10.0

10.5

Log GDP 1993

Fig. 1. Source: Calculations based on information by INEGI. Campeche and Tabasco are excluded from the sample.

262

National Border Baja California Coahuila Chihuahua Nuevo Leo´n Sonora Tamaulipas Northern central Aguascalientes Baja California Sur Durango Nayarit San Luis Potosı´ Sinaloa

Human capital indicators for individuals 15 years or older

Infrastructure indicators

Average schooling

Illiteracy rate

Railroads/100 Telephones/100 Percentage Agriculture Manufacturing Regional share Regional share km2 (km) persons of households (share of GDP) (share of GDP) in total number in total number of plants of employees with electrical supply

5.58 6.33 6.45 6.25 5.85 7.00 6.25 6.00 5.20 5.70 6.35 5.25 5.25 4.75 5.60

14.62 6.84 5.68 6.64 7.44 5.91 7.07 8.23 12.52 8.79 6.59 8.20 13.88 18.05 11.83

1.34 1.14 0.29 1.46 1.08 1.69 1.08 1.18 1.15 3.91 0.00 1.00 1.44 1.82 2.11

10.08 12.48 8.66 11.40 11.14 16.60 12.44 11.92 6.93 8.98 18.57 6.25 5.51 5.99 8.81

Economic orientation

81.29 86.38 89.10 90.50 80.95 92.75 84.55 80.35 77.31 89.55 82.15 81.20 85.15 62.70 82.85

9.42 10.01 10.25 8.71 15.99 1.70 20.27 13.10 19.34 7.64 12.31 21.84 20.81 10.36 25.71

24.84 24.15 17.15 29.07 18.29 37.14 13.37 13.55 17.44 27.63 7.60 23.02 17.10 27.98 10.05

Manufacturing plants with 250 or more employees

100.00 34.49 4.53 2.02 12.52 9.73 2.41 3.28 6.07 1.35 0.00 1.83 0.00 1.64 0.87

100.00 39.86 3.54 1.91 16.25 9.97 1.77 6.43 4.94 1.17 0.00 1.22 0.00 1.58 0.88

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Table 2 Regional indicators

4.60 4.77 5.75 4.25 4.45 5.50 4.30 5.70 4.65 4.95 5.35 4.55 7.03 7.90 6.05 4.21 3.35 5.35 3.65 5.20 4.75

12.19 18.77 11.00 20.11 25.03 10.89 21.05 14.23 22.79 20.09 13.71 20.74 7.86 4.91 11.17 29.46 33.99 31.00 31.53 14.58 17.43

0.92 2.45 3.83 3.52 3.61 1.28 1.91 5.54 3.03 2.63 8.96 2.45 6.30 21.16 5.27 0.60 0.73 0.16 0.73 0.00 1.58

3.28 7.19 10.42 6.51 4.38 11.26 5.50 10.24 6.29 6.37 3.02 6.36 17.19 27.27 7.20 4.50 3.09 5.41 2.69 9.93 8.25

73.30 76.84 88.15 79.55 66.20 86.90 77.85 90.55 76.20 73.05 87.70 66.50 94.38 98.35 89.85 64.47 54.65 66.75 60.80 77.20 84.20

26.58 12.24 18.06 12.52 10.26 11.02 17.77 7.74 10.94 6.99 13.46 13.96 1.53 0.23 3.99 21.02 29.69 15.86 25.11 8.54 10.21

4.36 23.60 6.13 22.14 31.27 26.81 12.55 26.29 25.82 39.50 30.98 18.55 31.92 27.53 40.20 8.71 6.56 5.07 11.16 5.69 16.36

0.39 16.67 0.00 2.22 0.39 4.62 0.39 0.29 3.66 1.45 0.67 2.99 42.20 18.30 23.89 0.58 0.00 0.00 0.29 0.00 0.29

0.08 18.80 0.00 1.69 0.60 7.64 0.26 0.39 2.79 1.20 0.48 3.75 35.96 15.64 20.33 0.44 0.00 0.00 0.19 0.00 0.25

Source: Based on figures from INEGI and NAFINSA. All data are for 1985, with the exception of the figures concerning manufacturing establishments, which correspond to 1988. The figures for schooling, illiteracy rates and households with electrical supply are averages of the corresponding figures for 1980 and 1990 published by INEGI (no published figures exist for 1985). Campeche and Tabasco are excluded from the data.

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Zacatecas Southern central Colima Guanajuato Hidalgo Jalisco Michoaca´n Morelos Puebla Quere´taro Tlaxcala Veracruz Mexico City Distrito Federal Me´xico South Chiapas Guerrero Oaxaca Quintana Roo Yucata´n

263

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the Mexico City market during 1970–1985. However, in order to avoid the high wages observed in that site, firms were gradually moving some low-skilled activities to nearby states where average wages were lower. This may explain why, during this period, growth tended to be higher in southern and central states surrounding Mexico City, but not in the city itself.4 In contrast, after the reforms, the U.S. market became increasingly important for Mexican firms, leading them to move northward in order to economize on transport costs. This may explain why after the reforms and, especially, after NAFTA was enacted, growth tended to be higher in the border region and exhibited a decreasing pattern with respect to distance to the U.S. It is important to mention, however, that some other site-specific features may have also been important determinants of the regional growth patterns observed after 1985. Apart from their proximity to the U.S. market, the border states may have exhibited other sitespecific external economies that may have promoted a higher growth rate in this region. These externalities, if they exist, may have become more important after the trade reforms. In effect, the states that have a border with the U.S. had relatively large endowments of communications, transportation and energy infrastructure, as well as of human capital, just before the reforms took place (see Table 2). This suggests that the border region may have offered both a better supply of public utilities and infrastructure and a relatively larger pool of educated labor force with appropriate skills to be employed in industrial, outward oriented activities, than most other regions of the country. In effect, a relatively high proportion of Mexico’s largest manufacturing plants was already located in the states that have a border with the U.S. when the reforms were enacted. These plants are usually foreign owned and account for most of the increase in manufacturing employment and export growth observed after Mexico’s trade liberalization and, especially, after NAFTA was enacted (see Lo´pez-Co´rdova, 2001).5 Note, however, that the high concentration of infrastructure and human capital in the border region may have itself been a consequence of the proximity of this region to the U.S. market. Some variables measuring the initial conditions in each state appear to have been relevant to explain which states attained larger increases in per-capita growth rates after the reforms took place. In particular, the scatter plots in Fig. 2 show the patterns of correlation between the change in each state’s growth rate from 1970–1985 to 1986–2001 and the levels, as of 1985, of some selected variables. According to these figures, states with higher levels of initial human capital, a higher concentration of large manufacturing plants, a lower concentration of agricultural activities and a higher availability of basic infrastructure at the beginning of the reforms, were in a better position to increase their subsequent growth rates. Thus, in principle the evolution of regional per-capita growth 4 Government policies also induced higher growth rates in some states within the southern region of the country during this period. For example, the exploitation of oil reserves by PEMEX induced higher growth rates in Campeche, Chiapas and Tabasco, while strong expansions of government expenditure at local levels influenced growth in Oaxaca. 5 In part, the high concentration of large, export-oriented and foreign owned manufacturing plants in the border states reflects the location choice of maquiladora plants. Most maquiladoras import all of their intermediate materials from the U.S. and sell most of their assembled goods to firms in that country. Therefore, in order to economize in transportation costs, these plants are usually set up in the Mexican side of the border with the U.S.

Per Capita Growth vs. Illiteracy Rate .02 .01 .00 -.01 -.02 -.03 -.04 -.05 -.06 -.07 .04 .08 .12 .16 .20 .24 .28 .32 .36

(Growth 1985-2001)-(Growth 1970-1985)

(Growth 1985-2001)-(Growth 1970-1985)

D. Chiquiar / Journal of Development Economics 77 (2005) 257–275 Per Capita Growth vs. Schooling .02 .01 .00 -.01 -.02 -.03 -.04 -.05 -.06 -.07 3

4

Per Capita Growth vs. Agricultural Share .02 .01 .00 -.01 -.02 -.03 -.04 -.05 -.06 -.07 .1

.2

.3

.01 .00 -.01 -.02 -.03 -.04 -.05 -.06 0.7

0.8

0.9

7

8

Per Capita Growth vs. Large Firm Presence

.01 .00 -.01 -.02 -.03 -.04 -.05 -.06 -.07

1.0

% of Households with Electricity, 1985

.01

.00

.02

.03

.04

% Large Manufacturing Firms, 1988 (Growth 1985-2001)-(Growth 1970-1985)

(Growth 1985-2001)-(Growth 1970-1985)

Per Capita Growth vs. Electricity Provision .02

0.6

6

.02

Agriculture's Share in Output, 1985

-.07 0.5

5

Schooling, 1985 (Growth 1985-2001)-(Growth 1970-1985)

(Growth 1985-2001)-(Growth 1970-1985)

Illiteracy Rate, 1985

.0

265

Per Capita Growth vs. Telephones/100Persons .04 .02 .00 -.02 -.04 -.06 -.08 0

5

10

15

20

25

30

Telephones/100 Persons, 1985

Fig. 2. Source: Calculations based on information by INEGI. Campeche and Tabasco are excluded from the sample.

across Mexico after 1985 appears to have been determined both by the kind of mechanisms implied by the economic geography literature and by the presence of other site-specific externalities in some regions. The following section addresses these issues more formally.

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4. Convergence across Mexican states The analysis made in the previous sections suggests that the convergent behavior across Mexican states’ per-capita output that was observed before 1985 broke down afterwards. As a consequence, a process of increasing economic differentiation across regions seems to have characterized the country from 1985 on. In this section, I test formally this hypothesis and assess if this result holds after controlling for differences in initial conditions faced by each state. Several authors have analyzed this topic previously. Mallick and Carayannis (1994), Juan Ramo´n and Rivera Ba´tiz (1996), Esquivel (1999), Messmacher (2000), Rodrı´guez Oreggia (2001), Garcı´a Verdu´ (2002) and Rodrı´guez-Pose and Sa´nchez-Reaza (2002a) studied absolute convergence across Mexican states. They all tend to conclude that convergence was a feature across Mexican states up to the mid-eighties, but that this pattern broke down afterwards. Most of these studies, however, used samples including regional growth rates at most up to 1996, so that the post-NAFTA growth experience is not fully taken into account nor analyzed explicitly.6 Moreover, a conditional convergence analysis is not conducted in any of these studies, even when this would be the natural step to follow given the findings concerning an apparent breakdown of absolute convergence. More recent papers by Esquivel and Messmacher (2002) and by Rodrı´guez-Pose and Sa´nchez-Reaza (2002b) extend the sample to 2000 and conduct conditional convergence analyses to study the regional effects of Mexico’s trade liberalization. The approach undertaken by these authors is closer in spirit to the one I apply here. However, in the first of these papers the conditional convergence regressions only include controls for schooling, distance to the U.S. and telephone density. This may be an insufficient set of variables to control for differences in steady state per-capita output levels. In the second paper a somewhat broader set of explanatory variables is used, although no controls for infrastructure are used and, in fact, most of the chosen regressors turn out to be statistically insignificant. While the main results obtained by these authors concerning convergence are similar to those I report here, in my analysis I use a broader set of explanatory variables, including communication and transportation infrastructure indicators, that turn out to be significant and apparently robust determinants of regional growth in Mexico. Moreover, by conducting additional analyses to control for region-specific unobserved fixed effects, I identify some important determinants of regional growth that previous authors were unable to distinguish.7 6 The only exceptions are Messmacher (2000) and Rodrı´guez-Pose and Sa´nchez-Reaza (2002a), who use more recent data and compare convergence during the post-NAFTA period with the patterns observed previously. The results of Rodrı´guez-Pose and Sa´nchez-Reaza (2002a) are consistent with other authors and suggest that NAFTA did not restore convergence. Messmacher’s (2000) results, however, contradict the findings of all other authors (he does not obtain statistically significant estimates for the convergence parameter b in any of his sample periods). 7 For example, in their cross-state growth regressions, Rodrı´guez-Pose and Sa´nchez-Reaza (2002b) are unable to find a significantly negative effect of distance to the U.S. on regional growth for the post-NAFTA period. I get similar results in the cross-state regressions conducted here. However, once I control for regionspecific fixed effects, distance to the U.S. becomes a significant factor explaining regional growth patterns in Mexico.

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4.1. Absolute convergence I first test for absolute b-convergence across Mexican states. If all states exhibit the same rate of technological progress x and have the same level of steady state percapita output y*, under a neoclassical model framework an empirical version of the equation describing the dynamic behavior of per-capita output is (Barro and Sala-iMartin, 1992):
   1 yi;t0 þT 1
e
bT log log yi;t0 þ ui;t0 d t0 þT ¼a
T yi;t0 T

ð1Þ

Here, y i,t 0 is the initial level of per-capita output of state i (at time t 0), y i,t 0+T corresponds to the final level of output per-capita in that state, after T years have elapsed, u i,t 0d t 0 +T is a distributed lag of the residuals of what would correspond to the one-period growth version of this equation, and a corresponds to: a¼xþ

1
e
bT log½ y4 þ xt0 T

ð2Þ

The parameter b measures the speed of convergence towards the (common) steady state per-capita output level. Under the absolute convergence hypothesis, we should expect this parameter to be positive. Evidence of a negative b would instead suggest divergence in per-capita output levels.8 Table 3 summarizes Non Linear Least Squares (NLLS) estimates for the parameters of Eq. (1) using data on Mexico’s states per-capita GDP and their growth rates for 1970– 2001 and for several sub-periods. The results support the idea that there are two distinct periods in terms of the comparative dynamics of per-capita output across Mexican states. In effect, the positive sign and statistical significance of the estimates of b for 1970–1985 support the hypothesis of absolute convergence up to 1985, while the significantly negative b estimated for 1985–2001 suggests that convergence broke down and divergence across Mexican states’ per-capita GDP was observed during this period. While the estimated b for 1993–2001 appears to be insignificant, once I control for the outlier described above (Quintana Roo), the results suggest that NAFTA did not break down this divergent pattern.

8 An important issue is that we cannot maintain the closed-economy assumption of the neoclassical model for the analysis in this paper: it is natural to expect some mobility of inputs, technology and goods across the states of the country. Concerning this point, Barro and Sala-i-Martin (1992) assert that, in this context, if technologies are the same, a rapid convergence in terms of per-capita output must occur, even when the presence of constant returns on the global capital market may avoid convergence in per-capita income. This justifies conducting convergence analyses for per-capita outputs across the regions of a country. Other relevant point to note is that, as Blanchard (1991) shows, if labor is not perfectly mobile across regions, in the absence of state-specific shocks regional convergence may be observed. However, if permanent state-specific shocks occur, regional divergence will eventually hold. In this context, if the effects of trade liberalization can be represented as region-specific permanent shocks and we assume labor is not perfectly mobile across regions, regional divergence after 1985 could be observed in Mexico, even if its states are not closed economies.

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Table 3 Absolute convergence results for various periods (t-statistics in parentheses) 1970–2001 1970–1985

a

0.0363 (1.380) b 0.0023 (0.724) T half2 304 R2 0.020 T (years) 31

1985–2001

Total

1970–1980 1980–1985 Total

0.1940 (6.144) 0.0224 (4.549) 31 0.511 15

0.2020 (3.830) 0.0210 (2.907) 33 0.270 10

0.2970 (2.183) 0.0340 (2.849) 20 0.260 5


0.1430 (2.480)
0.0146 (2.978) 48 0.201 16

1985–1993 1993–2001 1993–20011
0.2472 (2.256)
0.0246 (2.544) 28 0.160 8


0.0134 (0.344)
0.0030 (0.723) 231 0.018 8


0.0539 (1.553)
0.0072 (2.052) 96 0.128 8

All regressions exclude Campeche and Tabasco from the sample. 1 Regression excluding Quintana Roo. 2 T half=ln(2)/b is the half-life, i.e. the number of years it would take to reduce the current gap in per-capita output by a half. For the regressions corresponding to the periods 1985–2001, 1985–1993 and 1993–2001, it measures the number of years it would take to double the current gap.

4.2. Conditional convergence The heterogeneity in population and economic-related features across Mexican states may imply that the assumptions underlying the estimates described above may be too strong. If Mexico’s regions do not share the same steady state per-capita output, then the estimates could suffer from omitted variable bias and, in particular, could lead to an incorrect rejection of the convergence hypothesis (Sala-I-Martı´n, 1994). Thus, I now extend the analysis to study whether the lack of convergence across Mexican states found above remains after controlling for differences in each region’s steady state output levels. In particular, I conducted separate cross-state growth regressions for the periods 1970– 1985 and 1985–2001. Each of these regressions has the following structure:
 k   X 1 yi;t0 þT log bk Xi;t0 þ ui;t0 d t0 þT ð3Þ ¼ a þ b0 log yi;t0 þ T yi;t0 i¼1 That is, the growth regressions include as independent variables both the initial level of per-capita GDP and a set of k variables intended to control for differences in steady state per-capita output levels. This group of variables includes: i) average schooling years and illiteracy rates; ii) the interaction of schooling years and the log of initial per-capita GDP; iii) infrastructure indicators (telephone, electricity and railroad densities); iv) fertility rates; v) crime rates; vi) percentage of rural population; vii) federal investment and state government expenditures; viii) initial shares of agriculture and manufacturing outputs in GDP; ix) the percentage of manufacturing plants within each state that have over 250 employees; and x) a dummy variable for the states that have a border with the U.S. The 1970–1985 growth regression used data for these variables corresponding to 1970, while the second regression used data observed in 1985. Given the previous literature findings concerning the relative increase in the skill premium observed in the border after 1985, the border dummy was interacted with the schooling variable. Some additional schooling, health and financial indicators were initially considered, but did not appear significantly in any of the regressions.

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Table 4 GLS conditional convergence regression results Growth 1970–1985 Log initial per-capita GDP Average schooling years Log(initial per-capita GDP)*Schooling Telephones per 100 persons Federal investment (% of GDP) State expenditures (% growth in period) Agricultural output (% of GDP) Manufacturing output (% of GDP) % Large firms Crime Rate Illiteracy rate Rural population (% of total) Log(fertility rate) Railroads/size of state Dummy border states*Schooling % Households with electricity R2 Adjusted R 2

Growth 1985–2001

Coefficient

t-statistic

p-value

Coefficient

t-statistic

p-value


0.008 0.109
0.012 0.007 0.061 0.151 0.063 – 0.853 0.000 – 0.055 – –
0.001 0.064 0.878 0.803


4.857 7.434
7.616 6.634 3.534 5.861 4.058 – 5.488
4.587 – 4.257 – –
2.019 3.773

0.000 0.000 0.000 0.000 0.001 0.000 0.000 – 0.000 0.000 – 0.000 – – 0.052 0.001

0.055 0.091
0.011 0.004 – –
0.191
0.075 0.464 0.000
0.096 0.108 0.051 0.128 0.003 0.098 0.813 0.638

2.347 2.444
2.732 6.099 – –
6.106
4.292 2.206 1.746
2.625 4.539 3.757 2.404 3.428 2.891

0.025 0.020 0.010 0.000 – – 0.000 0.000 0.035 0.090 0.013 0.000 0.001 0.022 0.002 0.007

All regressions exclude Campeche and Tabasco. – indicates that the variable was omitted from the final specification due to the non-significance of its coefficient in the corresponding equation. Unimportant constant terms are omitted from the table.

Table 4 summarizes the results.9 Due to the limited sample size, as well as to the presence of collinearity between many of the regressors included, I estimated the equations with a Generalized Least Squares (GLS) estimator that accounts for possible correlation between the residuals of the equations for the two sample periods and, thus, allows for improved efficiency. I started with an initial estimate of the system and, following a general-to-specific modeling strategy, I sequentially tested and eliminated irrelevant variables, until I reached a parsimonious specification. The results still support the hypothesis that convergence in per-capita output levels across Mexican states broke down after 1985, even in a conditional sense. In particular, the signs of the coefficients for the initial level of per-capita GDP and for its interaction with schooling in the 1970–1985 regression support the presence of convergence and indicate that, holding the initial per-capita GDP level constant, poorer states with higher levels of human capital exhibited faster convergence rates (Barro, 1997). In contrast, for the 1985–2001 regression, the coefficient of initial GDP per-capita is positive, implying divergence in per-capita output levels. The interaction of initial GDP with schooling does appear with the expected negative sign but, given the sample mean for the

9

The results must be interpreted with care, since they are conditional on the set of independent variables chosen. We cannot rule out the possibility that, using a different set of conditioning variables, the results could be different. Indeed, this kind of regressions is extremely fragile to small changes in the conditioning information set (Levine and Renelt, 1992).

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schooling variable, the size of this coefficient is not large enough to offset the divergence result.10 According to the results, schooling seems to be an important determinant of growth. Note that, after 1985, the proportion of the population that is illiterate becomes a significant deterrent of growth. This suggests that, after that year, important deficiencies in basic education in some states may have inhibited their growth rates. The presence of communications and energy infrastructure also seems to be an important factor promoting growth. Moreover, an appropriate connection to the railroad network apparently became an important determinant of growth after 1985. As expected, this suggests that the reforms may have promoted relatively higher growth rates in states that have appropriate infrastructure to take advantage of enhanced trade opportunities. The shares of agricultural and manufacturing output exhibit interesting changes in their respective coefficients across the periods analyzed. The coefficient of agricultural output shifts to a large, negative value after 1985, suggesting that, after this year, agricultural states were especially affected in their growth performance. On the other hand, while for 1970–1985 the manufacturing’s share in output does not appear in the regression, for 1985–2001 this variable exhibits a slightly negative, but significant, value. However, the presence of large manufacturing plants in a state seems to have important positive effects on growth. These results may be reflecting the effect of a smaller protection to manufacturing after 1985 and may suggest that not all manufacturing activities, but only those that were exploiting economies to scale sufficiently to increase exports at low costs, were benefited. Also note that, after 1985, the coefficient for the interaction of the border dummy and schooling becomes positive and significant. This is consistent with the increase in the skill premium in the border region found in previous literature and suggests that, controlling for other effects, border states attained strictly higher growth rates after 1985, as compared with the rest of the country. In the growth regressions conducted here, however, a variable measuring distance from each state to the U.S. never appeared significantly. I will turn to this issue below. Finally, it is interesting to note that both the federal investment levels on the states, as well as the growth of state governments’ expenditures, had a positive effect on growth before 1985. This effect, however, disappeared in 1985–2001. This may reflect the fact that, while during 1970–1985 overall growth of the Mexican economy was fueled by large increases in public expenditures, which were financed mostly through international borrowing, after 1985 public expenditure was financed in a higher proportion through increased taxation. 10 I tried different estimation procedures to assess if the result of a lack of conditional convergence after 1985 was robust. First, since some of the data used for 1985 (schooling, rural population, illiteracy rates) were averages of the corresponding series for 1980 and 1990, I used their values as of 1980, as well as other economic indicators measured in 1980, as instrumental variables for their 1985 values. This approach did not alter the main results. I also estimated the model with robust regression techniques (Subramanian and Carson, 1988), again without obtaining different qualitative results. Finally, I extracted a set of principal components from the full set of available state indicators and estimated the growth equations using initial GDP per-capita and the set of principal components accounting for approximately 70% of the variability in the data. The results concerning divergence in per-capita GDP were not different from what was found before.

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I performed some hypothesis tests to evaluate if the apparent structural change in regional growth patterns after the opening up of the economy is statistically significant. I first forecasted the growth rates in the second period using the coefficients from the first regression. I also conducted a Wald test for equality of coefficients across the two equations. In both cases, the tests strongly reject the null hypothesis of no structural change. In conclusion, the evidence suggests that the states that had sufficient availability of communications and transportation infrastructure, a higher presence of large firms with export capabilities and a relatively well educated labor force were in a better position to face successfully the reforms and, as a consequence, attained higher growth rates. The states that satisfy these features are typically those closer to the U.S. border. In contrast, states whose population is more concentrated in agricultural activities and that exhibit important lags in terms of literacy rates, physical infrastructure and industrialization, were hurt by the reforms. 4.3. Additional results As seen in Section 3, some site-specific features seem to have been especially relevant to explain which states attained larger increases in per-capita growth rates after the trade reforms. The analysis I undertake here controls for state-specific (time-invariant) fixed effects on growth rates, by determining which variables explain significantly the change in the states’ growth rates after trade liberalization. In particular, I conduct a regression analysis for the change in growth rates from 1970–1985 to 1985–2001 as a function of the independent variables used previously:

 k X 1 yi;2001 1 yi;1985 log bk Xi;1985 þ ei;1985:2001
log ¼aþ 16 15 yi;1985 yy;1970 i¼1

ð4Þ

Among X i,1985 I initially included only the set of indicators used in the previous section and did not consider the effect of distance to the U.S. This variable was included in a second step. Consistently with the approach applied before, I reduced the equation to a parsimonious representation by sequentially testing and eliminating statistically insignificant variables. The results from this analysis are summarized in Table 5. The first three specifications in the table require an explanation. The first regression contains the set of variables that appeared to be significant after the specification search, plus the percentage of large manufacturing plants and the dummy for the border states. Although these variables appear to be individually insignificant, a joint significance test rejects the null that both coefficients are zero. Indeed, as shown in the second and third specifications, each of these two variables by itself tends to appear significantly in the regression. This suggests that the two variables may be measuring roughly the same effect. From specifications (b) and (c) it seems that the concentration of large manufacturing firms appears to be the relevant variable to keep. This suggests that, holding other factors constant, the border states attained higher growth rates, basically, because there is a large concentration of large firms in this region.

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Table 5 Growth shifts regression results Independent variables (1985)

(a)

(b)

(c)

(d)

Agricultural output (% of GDP) Illiteracy rate State expenditures (% growth in period) Dummy (Tlaxcala=1) Manufacturing output (% of GDP) % Households with electricity % Large firms Dummy (Border states) Log(Distance to US) Log(Distance to US) squared R2 Adjusted R 2


0.120


3.676
0.121


3.577
0.115


3.646
0.169


4.080


0.048
0.175


1.893
0.053
2.735
0.162


2.266
0.054
2.711
0.176


2.165
0.069
2.711
0.132


2.481
2.040


0.041


13.354
0.042


14.797
0.042


13.788
0.036


9.616


0.068


3.400
0.073


3.496
0.058


2.934
0.100


4.033

Coefficient t-statistic Coefficient t-statistic Coefficient t-statistic Coefficient t-statistic

0.034

3.958

0.035

4.304

0.033

4.001

–

–

0.293 0.005

1.189 0.800

0.446 –

2.220 –

– 0.008

– 1.475

0.322 –

–

– –

– –

– –

– –

– –

– –

0.843 0.793

0.837 0.795

0.836 0.793

0.020
0.002

1.715

3.998
3.342

0.847 0.798

All regressions exclude Campeche and Tabasco. t-statistics are computed using White heteroskedasticity-consistent standard errors. The regression included a dummy variable for the state of Tlaxcala, the smallest state in Mexico, to control for the fact that this state exhibited a large, unexplained negative shift in its growth rate.

It would be interesting to know if this concentration of large firms and its effect on growth is, at least in part, a result of the geographical advantage the border has with respect to the U.S. market. While testing this hypothesis may require a more structural approach than the one taken here, the results from specification (d) may give a hint. In this specification I add as additional regressors the log of the distance of each state to the U.S. border, as well as this variable squared. In contrast with the regressions conducted in the previous subsection, here distance to the U.S. appears to be a significant factor explaining growth patterns after 1985. Once this effect is taken into account, the significance of the variable measuring the concentration of large firms diminishes markedly (although it remains marginally significant at a 10% level). Thus, while the presence of large manufacturing firms seems to have a positive effect on growth, the results suggest that the geographical advantage of the border region is what may have caused this concentration of large firms in the past and may be behind the effect of this concentration of large firms on growth. Indeed, the results imply that, after controlling for the effects of the remaining variables in the regression, growth during 1985–2001 tended to be smaller as we move south from the U.S. Considering the results above, the evidence tends to support the economic geography type of arguments discussed in the first section of the paper. After the reforms took place,

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border states were especially benefited from the opening up as a result of their proximity to the U.S. market.11 This proximity may have itself been a determinant of the higher relative levels of development in this region before the reforms. However, as expected, this location advantage apparently became more important as a factor promoting growth after Mexico opened up to trade. Thus, even if some initial conditions may have also been favorable, it appears that the main driving force behind the relatively higher growth rate observed in the border region is related to its proximity to the U.S. market.

5. Conclusions This paper suggests that, after 1985, growth patterns across Mexican regions became more sensitive to new sources of growth. In particular, the kind of spillover effects implicit in many endogenous growth models seems to have gained relevance to determine growth patterns within Mexico after 1985. It is important to emphasize, however, that the results do not necessarily imply a rejection of the neoclassical growth model. The results could also be consistent with the transitional dynamics of a neoclassical model in which a structural break took place. In any case, this break seems to be a consequence of Mexico’s trade reforms. Only some of the relatively richer states had appropriate infrastructure to take advantage of the new sources of growth derived from enhanced opportunities to trade. Therefore, the reforms apparently induced a process of regional divergence in per-capita output levels. In particular, the regions that are closer to the U.S. border seem to have reaped most of the benefits from the reforms, apparently, as a consequence of their proximity to the U.S. market. However, other unrelated location-specific externalities may have also been relevant to promote growth in this region. In effect, border states were endowed with higher levels of human and industrial capital and better communications and transportation infrastructure when the reforms were enacted. Identifying the relative importance of each possible mechanism, as well as exploring to what extent locationspecific externalities interacted with trade liberalization to determine growth patterns, requires a more structural approach than the one taken in this paper. In any case, it is clear that Mexico’s liberalization has increased the ties between northern Mexico and U.S., at the same time that the ties between northern and southern Mexico have weakened. This may indicate that, as Hanson (1998b) and Quah (1996) 11 Another independent factor that may have promoted higher growth rates in outward-oriented regions than in states close to large domestic markets during 1985–2001 may be the recurrent collapses in domestic demand derived from devaluations of the currency and, in particular, from the peso crisis of 1994–1995. If this is the case, the results in Table 5 could suffer from an omitted variable bias, since the regressions do not control for domestic factors. To analyze this possibility, I included as an additional regressor a variable measuring the log of distance from each state to Mexico City. This variable did not appear significantly in any regression and, moreover, its inclusion did not affect the significance or magnitude of the other coefficients. These results may reflect the fact that most real exchange rate devaluations observed during this period were undone relatively quickly by offsetting real appreciations of the currency. Thus, the real exchange rate movements observed during this period may have promoted higher growth rates in outward-oriented regions at most only temporarily, and not in the medium term. I thank an anonymous referee for pointing out this issue.

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suggest, it increasingly makes sense to take regions, as opposed to nations, as the unit of analysis in international trade and convergence issues.

Acknowledgements I thank Kate Antonovics, Julian Betts, Richard Carson, Rodrigo Garcı´a Verdu´, Theodore Groves, Gordon Hanson, Mark Machina, James Rauch, Julio Santaella, Chris Woodruff, the participants at the Wider/Cornell/LSE Mexico Conference on Spatial Inequality in Latin America held at Universidad de las Ame´ricas, Puebla, during November 2–3, 2002 and two anonymous referees for very helpful comments. I also acknowledge the Consejo Nacional de Ciencia y Tecnologı´a (CONACYT) for financial support. The opinions in this paper correspond to the author and do not necessarily reflect the point of view of the Banco de Me´xico.

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