Guide Development and Growth in the Mexican Economy: A Historical Perspective

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Computadora de escritorio. Sinopsis This book is the first comprehensive and systematic English-language treatment of Mexico's economic history to appear in nearly forty years. Drawing on several years of in-depth research, Juan Carlos Moreno-Brid and Jaime Ros, two of the foremost experts on the Mexican economy, examine Mexico's current development policies and problems from a historical perspective.

They review long-term trends in the Mexican economy and analyze past episodes of radical shifts in development strategy They review long-term trends in the Mexican economy and analyze past episodes of radical shifts in development strategy and in the role of markets and the state. This book provides an overview of Mexico's economic development since Independence that compares the successive periods of stagnation and growth that alternately have characterized Mexico's economic history. It gives special attention to developments since , and it presents a re-evaluation of Mexico's development policies during the State-led industrialization period from to as well as during the more recent market reform process.

This reevaluation is critical of the dominant trend in economic literature and is revisionist in arguing that, in particular, the market reforms undertaken by successive Mexican governments since have not addressed the fundamental obstacles to economic growth. Previous Edition Praise — Multicultural Review [This] brief but comprehensive survey emphasizes economic, social, and demographic changes along the U.

Previous Edition Praise — Linda B.


Hall, University of New Mexico A major interpretation of one of the world's most intriguing areas—the U. To date, the very best single synthesis of the salient themes and issues of the twentieth-century border. Previous Edition Praise — David R. Maciel, California State University A well-organized and highly readable study of the border as a frontier, an international boundary, and a region.

The authors take a complex subject and make it understandable, even for those with little or no familiarity with the theme. The range of topics and the breadth of the time period covered are well conceived. The authors clearly demonstrate the accuracy of their observation that the reality of the border is far more interesting than popular myths and stereotypes suggest.

Previous Edition Praise — Don M. Coerver, Texas Christian University. Accessibly written for students and general readers as well as practitioners and researchers Relevant and up-to-date statistical data are provided in clearly presented tables to facilitate discussion and analysis Original photographs and maps enable the reader to better understand the geography, society, and culture of this dynamic region Includes up-to-date discussions of key issues in the U.


This measure obviously involves a scarcity problem, particularly of natural resources like diamonds and uranium, for example. Non-ubiquitous goods can be divided into those with high technological content, which are therefore difficult to produce airplanes , and those that are highly scarce in nature, such as diamonds, which are therefore naturally non-ubiquitous. To control for this issue of scarce natural resources in complexity measurements, the authors of the Atlas use an ingenious technique: they compare the ubiquity of the product made in a given country with the diversity of the exports of countries that also produce and export this good.

To illustrate: Botswana and Sierra Leone produce and export something that is rare and therefore non-ubiquitous, rough diamonds. On the other hand, their exports are extremely limited and undiversified. These, then, are instances of non-ubiquity without complexity. At the opposite end of the ubiquity spectrum we could mention image-processing medical devices X-ray equipment which practically Japan, Germany and the United States complex countries alone can manufacture and export; these are non-ubiquitous complex products.

In this case the export composition of Japan, USA and Germany is extremely diversified, indicating that these countries are highly capable of making many different things. On the other hand, countries with highly diverse export composition made up of ubiquitous goods fish, meat, fruits, ores, etc. Diversity without non-ubiquity means lack of economic complexity. One of the main virtues of such economic ECIs and product complexity PCI indicators is the fact that they operate based on quantitative measures obtained from linear algebra calculations to arrive at their results.

There is no account of qualitative issues relating to the production and exports of those goods. That is, no judgment is made as to what is regarded as complex or non-complex. Along these lines, the authors rate several countries and arrive at robust correlations among income per-capita levels, inequality and economic complexity Hausmann et al.

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Japan, Germany, Switzerland and Sweden are always ranked among the top ten countries in terms of complexity. Economic development may be treated as the mastery of more sophisticated production techniques, which usually lead to output of higher value added per worker as argued by classic development authors. This is what economic complexity indicators ingeniously capture from measures of ubiquity and diversity of exports from various countries.

To illustrate: countries that make advanced combustion engines probably have engineers and knowledge that enable them to produce a series of similar and sophisticated things. Countries that only produce bananas or other fruit have limited knowledge and are probably incapable of making more complex goods. It is important to emphasize that the difficulty observing these differences arises from our inability to directly measure and capture such local productive skills.

Commodities in general lack these characteristics. Empirically, the Atlas clearly shows that manufactured goods are generally characterized as more complex and connected whereas commodities emerge as non-complex and non-connected goods.

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Out of the 34 main communities of goods in the Atlas calculated by their network compression algorithm Rosvall and Bergstrom, , one finds that machinery, chemicals, airplanes, ships and electronics stand out as the more complex and connected goods hubs of knowledge. On the other hand, gemstones, oil, minerals, fish and shellfish, fruit, flowers, and tropical agriculture show very low complexity and connectivity.

Grains, textiles, construction material and equipment and processed food occupy an intermediate position between more and less complex and connected goods. If poor countries are growing faster than rich ones, there has been GDP per capita convergence, but if rich countries are growing faster one can conclude that there has been divergence.

Although being conceptually not so precise as the first approach, the second approach has some advantages. By using controls in econometric regressions, in the beta-convergence approach it is possible to differentiate conditional convergence from unconditional convergence. However, in this approach it is possible to add control variables such as presented in equation 2. These controls enable us to analyse the existence of conditional convergence - or convergence when all other variables remain unchanged.

Again, in this analysis, if one finds a statistically significant negative beta coefficient one can conclude that there is conditional convergence because low-income countries are growing faster than high-income countries if all other variables remain unchanged. The most appropriate econometric technique to tackle this issue seems to be heterogeneous regressions 8. The Economic Complexity Index ECI will not be used as a control variable in the baseline equation, but as a variable of heterogeneity.

Since our dataset consists of countries with different degrees of complexity, we can add an interaction term between GDP per capita and ECI to the regression model in order to capture the impact of exports complexity on conditional and unconditional convergence. This estimate may shed light on some important issues in the current debate concerning the effectiveness of promoting export sophistication for boosting growth. Let us begin by analysing the impact of GDP per capita on output growth without considering the heterogeneous effect provided by the inclusion of the ECI on the regression.

The model to be estimated follow the basic structure of the model presented in equations 1 and 2. This estimator extends the standard Arellano and Bond GMM estimator by utilising lagged differences as instruments for equations in level and lagged levels as instrument for equations in first difference. Hence, there is no need to find exogenous regressors as instruments for the GDP per capita, for the variables used as controls and for the variables used to assess the heterogeneous effects. Thereby, the following model is estimated:. Differently from equations 1 and 2 , where the coefficient of ln GDPpc i,t—1 refers to the convergence coefficient, in dynamic panels, where a lagged variable of the dependent variable is included in the regression, it works a short-term coefficient.

Time series for income growth are taken from the Penn World Table 8.

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There is a number of variables that can be used to explain growth. In order to enhance comparability, we decided to take into account government expenditure as a share of GDP, population growth and exports as a share of GDP. These models argue that government can be a heavy burden on the economy when they impose high taxes, promote inefficient programs, do not eliminate unnecessary bureaucracy, and distort market signals. The proxy commonly used to account for the government burden is the ratio of government current expenditures to GDP.

However, neoclassical economists, by and large, also acknowledge the importance of public investments on health, education, and security to promote growth. Finally, exports as a share of GDP is used as a proxy to export-orientation. This work consists of a sample of countries and covers the period Our estimates were done based on four-year period averages.

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This is a standard procedure in panel data analysis, as it reduces the effects caused by unit roots. Table 1 presents the results for the regressions without controls unconditional convergence and with controls conditional convergence :. Long term impact: long-term impact of undervaluation on growth rate; calculated based on equation 4. The inclusion of controls in estimation 2 indicates that other variables may impact on countries growth rate. Government expenses as a share of GDP impact negatively, whilst population growth and exports as a share of GDP impact positively.

Nevertheless, the inclusion of these variables does not change the main result of our estimation. The beta-coefficient the coefficient associated with convergence or divergence remains statically equal to zero. The value of this index varies significantly for countries in the same stages of development. The Chinese ECI, on the other hand, was around 1. Although not so significant, variation is also verified in developed countries.

Development and Growth in the Mexican Economy: A Historical Perspective

The main idea behind complexity is that the higher is the economic complexity of a country, the better are its conditions to promote faster growth rates. We analyse this by using heterogeneous regressions. Firstly, the following model is estimated:.

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This term, which is the multiplication of the log of GDP per capita and the ECI for a given period which in our analysis is , is the one that enable us to interpret the relation between growth and GDP per capita not linearly but as a linear function of the ECI. The beta coefficient the long term relationship between GDP per capita and growth is now given by:. The results of this estimation for unconditional and conditional convergence is presented in Table 3 :.

It indicates that countries with high export complexity are more capable of reducing the income gap to developed countries than countries with low export complexity. The conditional convergence coefficient can be estimated for each country based on equation 6. In the case of countries which the ECI is close to zero, such as Brazil, Indonesia, South Africa and Russia, the convergence coefficient is calculated ignoring the parameter of the interaction term, such as in equation 4.

For these countries, the beta coefficient the long-term relationship between GDP per capita and growth is 0.