Studies at the OFDI Flows Level

The literature roughly identifies market size, agglomeration economies, political environment, exchange rate, natural resource endowment, technology, and culture as the main determinants of Chinese OFDI. These factors differ according to the destination region and the type of project: while greenfield projects allow companies to penetrate sectors where they have well-developed capabilities, M&As allow them to ensure the supply of natural resources in LAC, and access to technology leading in Europe and North America (^{ECLAC, 2021}). The incentives differ depending on the agent: while public companies pursue China’s strategic needs and invest in natural resources through M&A, private companies consider political risk and are therefore guided by demand prospects and strategic assets (^{Dreger, et al., 2017}).

A group of recent investigations provide empirical evidence in such aspects:

Studies at Company Level

In 2016 ^{CAITEC, MOFCOM, et al. (2017)} applied a questionnaire to 543 Chinese companies operating in OBOR countries. Among the characteristics of the companies, it was found that: 59 percent are private; 45 percent have operated abroad for more than 10 years; a third showed an investment scale of more than 100 million dollars (md); 55 percent belongs to the manufacturing and construction industry; 51 percent enter through new investments. The questionnaire provides an indirect understanding of some of the motivations behind the internationalization strategy of Chinese companies in the OBOR region:

Studies of Chinese companies in LAC identify uncertainty and the investment maturation/learning period as determining factors. The lack of information from the Chinese company regarding specific issues (e.g., suppliers, customers, regulations), as well as the little knowledge of the LAC governments about Chinese companies (^{Dussel Peters, 2019}) are conditions that increase the uncertainty factor, which, in turn, adversely impacts profitability. At the country level, the following stand out:

In sum, an expanding domestic market, a qualified labor force, the presence of seaports, the proximity to the United States, the benefits of NAFTA, and the strength of the industry, are incentives for Chinese OFDI in Mexico. In contrast, the uncertainty factor and psychic distance are factors that inhibit investment.

Regional and Local Determinants: The Forces of Agglomeration

Productive Structure of Microregions and Specialization. To examine the location factors of Chinese OFDI in Mexico from a regional perspective, the territorial areas were delimited for nine microregions in which the 11 Chinese companies identified in Table 1 are located. The delimitation of the spatial units of analysis was made based on the location of 11 companies in the automotive and auto parts sector depicted in Table 1. Based on the location of such companies, nine micro-regions were identified based on the methodological proposal of the Center for Regional and Sustainable Urban Development Studies (Cedrus) of the National Autonomous University of Mexico (Universidad Nacional Autónoma de México, UNAM), which groups the national territory into homogeneous areas. from local administrative units (^{Asuad, 2020}). The set of nine microregions is made up of 100 local demarcations that cover an area equivalent to 6.5 percent of the Mexican territory. Table 2 reports the results for the microregion of Aguascalientes, where the Minth company is located.

The Aguascalientes micro-region is made up of five municipalities: Jesús María, San Francisco de los Romo, El Llano, Aguascalientes and Ojuelos de Jalisco. The five municipalities have a total population of 1.2 million inhabitants and a population density of 340 inhabitants per square kilometer, more than three times the national average. The microregion has similar sociodemographic and development characteristics to the nine microregions, although, slightly more favorable in all indicators.

In the nine microregions, the relative share of employment and manufacturing value added is high. In the Aguascalientes micro-region, the relative participation of added value and the employed population is even higher with percentages of 66.13 and 36.32, respectively. Within manufacturing, the manufacture of transportation equipment represents 48.50 percent of the sectoral value added in the nine microregions, more than double compared to the national figure. The share of this subsector in the micro-region where Minth is located is 75.57 percent. The relative specialization or location coefficient corroborates the significant presence of manufacturing activity in the nine microregions, while the levels of relative specialization in manufacturing and the transport equipment subsector are even higher for the Aguascalientes microregion.

Spatial Distribution Patterns and Agglomeration Forces. The analysis of the agglomeration forces in the AAI was carried out through two elements: Moran’s spatial correlation indices and heat maps with kernel density. The National Statistical Directory of Economic Units (Directorio Estadístico Nacional de Unidades Económicas, denue for its acronym in Spanish) allowed spatially locating the economic units that were members of the AAI in the period 2010-2020. The AAI is made up of three branches: 3361 car and truck manufacturing; 3362 bodies and trailers manufacturing; 3363 parts for motor vehicles manufacturing.

Moran’s I was used to measure the global spatial autocorrelation in the set of microregions for the variable number of economic units per municipality of the three branches that make up the AAI. Spatial autocorrelation is “the functional relationship between the values that an indicator takes in a space zone and in neighboring zones” (^{Chasco, 2003: 50}). The indicator was estimated using ^{Anselin (2020)} and a queen-type spatial weight matrix of order 1 was used. Moran’s I measures the degree of linear association between the variable of interest and the average value of the neighbors’ variable, and its value is between negative one and positive one.

According to ^{Anselin (2020)}, Moran’s I is one of the most common measures to detect global autocorrelation, that is, the spatial correlation over the entire dataset. It is the variable (expressed in deviations from the mean) multiplied by the weighted average value of the neighboring variable. Following ^{Anselin’s notation (2020)}, and if z _i = x _i -x-, the Moran statistics is

Where is each one of the elements of the weight matrix that reflects the neighborhood or spatial structure, here we use a queen-type neighborhood structure of first order; while, S ₀ = Σ _i Σ _j w _ij is the sum of all weights and n is the number of observations. Moran’s I measures the degree of linear association between the variable of interest and the average value of the neighboring variable and its value is between negative one and positive one.

Between 2010 and 2020, the number of AAI economic units increased by 65 percent in the set of micro-regions, going from four hundred eighty to seven hundred ninety-six. The global correlation coefficient, Moran’s I, identified positive and significant spatial autocorrelation with a confidence level of 95 percent, although its value is relatively small, it has been increasing since in 2010 it was 0.18, while in 2020 it reached a value of 0.25. However, those values indicate a non-random distribution of the economic units of the AAI in the microregions considered. In other words, its spatial distribution accounts for patterns of spatial concentration that could be associated with agglomeration forces.

The heat maps are graphical tools that allow the identification of groupings or clusters based on the estimation of the kernel density. The kernel density consists of the calculation of “the density of points in a neighborhood around each output raster cell, which represents the characteristics of the point distributions” (^{Lu and Cao, 2019: 6}). In other words, the kernel density shows how dense the concentration of elements is in an area based on a point. The calculation of the kernel density for points, as it is in our case, is based on the classic work of ^{Silverman (1986)} in which the density is calculated as:

where i = 1, ..., are the points considered for the density calculation, which should only be included in the sum if they fall within the search radius of the neighborhood, which in our case was 45 thousand meters (radio) for the purpose of identifying concentrations on a national scale; meanwhile, pond _i is an element that allows weighting the importance of the points, usually it can be a value such as population, when pond _i = 1, each point is assigned the same relative importance, which was what here we meanwhile made dist _i the distance between point i and the reference location. The search radius used was 10 km and the raster cells were defined at a pixel size of 80 to generate discrete interpolation maps and equal intervals of four classes (Figure 1).

Source: Developed by the authors based on ^{INEGI (2021)}, indicated years.

Figure 1 KERNEL DENSITY 2010 AND 2020 OF THE ECONOMIC UNITS OF THE AAI IN THE MICROREGION OF AGUASCALIENTES 

The number of economic units belonging to the AAI in the Aguascalientes micro-region went from 48 to 91. In the two-time cuts, groupings of economic units were identified through this instrument. These clusters spread along Federal Highway 45, the so-called Pan-American Highway, which stretches from the border with the United States in Ciudad Juárez, Chihuahua, to the state of Hidalgo, in central Mexico. In addition, the density of economic units increased, going from a maximum threshold of 15 economic units in the search radius to one of 22 economic units.

In 2010, the highest density area in the microregion was identified south of the city of Aguascalientes, a group where the Minth company is located (Figure 1a). The southern grouping extends around the population center called Ciudad Industrial, with more than 15 AAI economic units in the search radius. The cluster extended to the north of the city, but with a gradually decreasing density. The main change identified in 2020 in relation to the previous time cut is that the highest area of density in the microregion moved north of the city of Aguascalientes, to the municipalities of San Francisco de los Romo and Jesús María, with a density of 22 economic units within the search radius, mainly around the San Francisco Industrial Park. However, the loss of importance of the southern part of the city is only relative, since in absolute terms the number of AAI economic units increased and spread further south, towards the city airport where the finsa industrial park is located, near which plant 2 of the Nissan assembly plant is located.

These results are an indication of the presence of agglomeration forces that affect the location decisions of companies operating in the AAI, both in the set of nine microregions (Moran’s I positive and significant), and at the level of the microregion of Aguascalientes, where two important groups are identified, one to the south (where Minth is located) and another to the north.

Microeconomic Factors: The Case of the Minth Company

In November 2019, field work was carried out at the Minth plant located in Aguascalientes, Mexico. A year later, in November 2020, a virtual semi-structured interview was conducted with the plant’s director of sales and infrastructure. The interview was part of the UNAM-PAPIIT IA302620 Program “Las empresas chinas en la industria de autopartes y automóviles en México: condiciones actuales y perspectivas ante el Tratado México-Estados Unidos-Canadá (T-MEC)”. The authors thank Ing. Manuel Yoshiro Ando Camacho for the interviews granted. They also state that they are solely responsible for the information contained in the document.

The information collected was triangulated with the review of various financial reports of the parent company, conferences, specialized press, and other documents that allowed the construction of the case study from a triangular approach (^{Yin, 2014}).

Minth Group. Minth Group Limited was established in 1997 and has its predecessor in Xiaogang-based Ningbo Minfu Mechanics Plant. It is one of the 100 global auto parts companies that develops activities of design, manufacture and sale of moldings, decorative parts, and metallic aluminum structural parts that are supplied to the main assemblers in the world. 51 percent of its sales revenue comes from GM, Nissan, and Honda. It has more than 50 plants and a workforce of 17,812 workers (^{Minth Group Ltd., 2021}). Its manufacturing centers are located in China, the United States, Mexico, Thailand, Germany, Serbia, the United Kingdom and the Czech Republic. Its sales, design and research & development (R&D) centers are located in China, Germany, the United States, Japan and Korea.

In 2020, the group’s income fell by 5.5 percent, causing gross profit to contract at a rate of 6.2 percent. The gross profit rate stood at 31 percent, experiencing a decrease of 0.2 percentage points compared to 2019. The slight drop in the profit rate was mainly attributed to the decrease in the utilization rate of installed capacity, due to the drop in sales revenues in 2020 derived from the impacts of the pandemic, and the pressures in the decrease of merchandise prices for older models and higher tariffs on Chinese products in the United States. These negative trends outweighed other trends with a favorable impact on the profit rate: the start-up of new production lines and the launch of various stimulus policies for economic recovery by the Chinese government. In short, the corporate profit rate has fallen particularly sharply since 2009, but the investment rate has multiplied by 2.6 times.

In a context of crisis, Minth Group increased its spending on physical investment, its investment rate was 51 percent in 2020. This was attributable to the expansion of R&D activities in battery-housing, an active implementation of intelligence development strategies, and the initiative to establish an intelligent industrial park for the car of the future, all of which are consistent with the global trend of the automobile industry (^{Minth Group Ltd., 2021}). This makes it clear that, in its investment decisions, the group follows the demand perspectives of global automakers.

Between 2009-2020 Minth Group reduced by 25 percentage points the relative share of its revenues originating from its clients located in China and increased the share of sales from its clients located in North America and Europe by 11 and 14 percentage points (see Table 3). In other words, since 2009 Minth has increased its insertion in global automotive value chains around Europe and North America.

Minth Mexico. Minth México started operations in 2009 through the acquisition of a Japanese logistics plant, beginning with the assembly of auto parts for its only client at the time: Ford. In 2014, through a JV with the Japanese Tokai Kogyo, it opened an anodizing plant for premium vehicles, but the alliance failed and by 2016 the plant became controlled by the Japanese firm. In 2015 Minth invested approximately 50 million dollars for its new aluminum extrusion plant. Currently, the company specializes in four processes: sheet rolling, plastic extrusion, aluminum anodizing, and aluminum extrusion, with the following characteristics: low levels of competition in Mexico (in rolling, it has three competitors; in aluminum, it has one competitor, and in both cases, they are foreign subsidiaries); high technical requirements and high risk due to the cost of the process.

Currently, the plastics and stamping plant supplies conventional customers (Nissan, GM, Volkswagen, and Ford) and 70 percent of its sales are exported. The aluminum plant supplies premium customers (BMW, Mercedes-Benz, Volvo, Audi, GM) and 90 percent of its sales are exported. The company replicates the industrial organization of the auto parts segment in Mexico, its main feature being the high dependence on imports, for example, about 90 percent of the inputs are of U.S. origin and the rest is from Asian and Mexican suppliers. Similarly, 98 percent of the raw material is imported.

It is a large company, with productivity levels similar to those of the parent company, although the cost of production is still 30 percent lower in China. Between 2009-2018, it reported an average annual growth in sales of 68 percent. Minth México is a relevant case because it is the first Chinese company that came to the Mexican AAI and the one that has developed the most investment projects. Among the contextual factors that explain the growing presence of the foreign subsidiary, the following stand out:

It is interesting to point out that the internal monetary policy reflected in the behavior of the interest rate does not seem to be a factor for the expansion of Minth in Mexico, since the new investments are completely financed with resources from the parent company (which, in turn, obtains financing through public institutions in China and through its participation in the stock market), while the capital increases are financed by the subsidiary in Mexico through the reinvestment of profits. On the other hand, the behavior of the exchange rate affects the decisions of the subsidiary because the depreciation processes of the peso-dollar exchange rate stimulate the Chinese OFDI since it generates savings through labor costs. Due to its growing international expansion and strong fluctuations in the foreign exchange market, the Minth Group carefully follows exchange rate expectations when deciding on the billing currencies of its relevant businesses (^{Minth Group Ltd., 2021}).

More than a decade after the arrival of Minth in Mexico, three major problems can be identified that reflect the learning and adaptation processes that the subsidiary has gone through:

Finally, the USMCA can cause two effects for Minth Mexico. On the one hand, it could mean higher sales in the United States, on the other, it could lead to a loss of regional competitiveness with Asia, particularly due to the steel chapter in the agreement. In effect, the new agreement forces companies to buy steel and aluminum from companies in the region and particularly from the United States, all of which will have an impact on costs. The auto parts companies will have two years to look for suppliers of steel and aluminum from the United States or Mexico. Focused on Mexico, the task is not minor, considering that the structural steel industry is practically a transnational oligopoly and because of the incipient aluminum industry. Minth is currently seeking to develop suppliers in Mexico, but given the price, quality and production scale requirements, only large companies (typically MNEs) have the potential to participate as suppliers.