A literature review of offshoring and the Stolper-Samuelson Theorem

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Bachelor Thesis

Name: Yijie (Fllay) Gu

Student number: 10256369

Specialization: Economics and Finance

Field : Globalization

Title of the thesis: A Literature Review of Offshoring and

the Stolper-Samuelson Theorem

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During the last few decades, U.S. based international companies have grown not only in numbers, but also in scale. However, its domestic employment has been diminishing gradually. This, a priori, may relate to offshoring, which is an increasingly significant element of international trade (Harrison and McMillan, 2010). International trade consists primarily of exports and imports. It has increased from only 5 percent of the world GDP to more than 25 percent since World War Two. One noted feature of this trend of globalization is that trade in manufactured intermediate goods as well as service between development economies and developing economies. This feature of international trade is referred to as offshoring, or sometimes as international outsourcing (Geishecker, Riedl and Frijters, 2012). Developing countries, including China and India, take offshoring or outsourcing to integrate into the global value chains. The World Development Indicators database (2008) states that the percentage of manufacturing merchandise trade in gross domestic product (GDP) in the low- and middle-income countries increased from 31% to 57% between 1990 and 2007. There is also large change in foreign direct investment in South and East Asia, in which the percentage of inwards FDI in GDP increased from 9.3% to 26.8% between 1990 and 2003. Countries can incur substantial gains from offshoring strategies of its companies as long as the policy makers understand the magnitude and the nature of the labor market effects of these offshoring strategies (Crino, 2009). While boosts in foreign investment and exporting activity increase the likelihood of additional wage and more employment for the developing country, trade theories such as Stolper-Samuelson theorem, which will be

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discussed in the following part of the paper, suggests that trade openness does not ensure a win-win situation; rather, it will lead to both winners and losers with respect to unemployment and drop in wage for some sectors (Robertson et al. 2009).

In this paper, the research question is ‘Has material offshoring resulted in raising skilled-labor demand while cutting down unskilled-labor demand in all sectors?’ I focus on material offshoring by first explaining in detail what offshoring is and the difference between offshoring and other forms of international trade. Secondly, based on the study of Crino (2009), I explain the Stolper-Samuelson theorem it mentioned but not discussed. Thirdly, I draw attention to the literature by Bernard and Jensen in 1997 which Crino (2009) has mentioned but didn’t elaborate and its contradiction with Stolper-Samuelson theorem. Finally, I conclude that material offshoring, at least including which took place in 1973-1987, does not comply with Stolper-Samuelson theorem in the aspect that it increases the employment rate of skilled-labor while worsens the unemployment rate of unskilled-labor.

2. Literature Review

2.1 What is Offshoring?

Offshoring is used to describe the situation in which a firm relocates some stages of production abroad, to either one of its affiliates or an unaffiliated

supplier. What are the differences between offshoring, outsourcing and exporting then? ‘Offshoring is the sourcing of inputs (goods and services) from

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foreign countries’ according to Mitra and Ranjan (2010). The dictionary states that offshoring is the movement of jobs by corporation from one nation to another in an effort to lower costs or improve service (dictionary.com, 2006). Sako (2005) explained it in more details, stating that two separating decisions must be made before starting one business firm or public sector organization. The two decisions are about the boundary of the organization and the location of its activities. If optimal, firms can choose to ‘buy’ instead of ‘make’ good and service inputs in-house. Offshoring happens when firms move part of its value chain overseas, whereas outsourcing switch from sourcing inputs in-house to sourcing them from external suppliers. Exporting is an entirely different activity, which means to sell own products to foreign countries. On top of the definitions mentioned above, there are four complications. The first is that firms that are outsourcing already can switch to an international supplier from a domestic one. Second is that they can simultaneously outsource and offshore to an international supplier. Third is that they can set up an affiliation in order to source from foreign countries. Fourth, the firms can decide to sell the overseas affiliates to local firms and keep sourcing from them. Figure 1 illustrates the definition of outsourcing and offshoring. The study will be focusing on the US as an offshoring country. The reasons that I choose the U.S. are that it is both significant with respect to offshoring and employment rate. News release from U.S. department of commerce, bureau of economic analysis shows that employment in a global scale by U.S. multinational companies increase 1.5 percent in 2011 to 34.5 million workers; the increase mainly consists of employment increases abroad. Employment by majority-owned foreign affiliates of U.S. multinationals increased 4.4 percent to 11.7 million workers. Thus it can be concluded that the U.S. plays an important role in offshoring and employing

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foreign labor force. The CIA World Factbook indicates that the U.S. is the top-rank country by the stock of Foreign Direct Investment abroad, accumulating

4854 billion, estimated in 2013.

To specify even more, there are two modes in offshoring: one is called ‘production transfer within multinational enterprises (MNEs), because production activities remain within the same MNE; the other one is

‘international outsourcing, because activities are licensed outside the firm in means of contracts’. Crino (2009) specializes the definition of offshoring according to the type of activities that are relocated abroad, which includes the broader definition of both modes. Moreover, within, there are two types of offshoring: material offshoring and service offshoring. Material offshoring depicts the relocation of production activities, such as assembly lines. Service offshoring depicts the relocation of service activities, such as call center operations. Within the MNEs， there is the orthodox classification of foreign

direct investment: vertical FDI and horizontal FDI. Vertical FDI concerns the transfer of different stages of production abroad, meanwhile horizontal FDI concerns the replication of the same activities as found domestically abroad.

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Horizontal FDI serves to alleviate transportation costs and trade barriers when dealing with international markets (Brainard, 1997). However, offshoring doesn’t have to happen in MNEs, and vice versa, MNEs don’t have to obey offshoring strategies only.

2.2 The expansion of material offshoring

The below figure goes into the expansion of material/manufacturing offshoring. The solid line indicates the trend in material offshoring by US manufacturin g industries between 1997-2002, which is estimated by Feenstra and Hanson in 1996 and 1999 using the share of imported intermediate inputs in total non-energy input purchases as the proxy of material offshoring. They found the trend has increased from 5.1% to 18.1% in 1972 to 2002. Not only in the US, but also in nearly all other developed countries, similar trends can be found. Take Canada as an example, between

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1974 and 1993, the share of imported intermediate inputs in total non-energy input purchases in Canadian manufacturing sector has increased from 15.9% to 20.2%, according to Campa and Goldberg in 1997.

3. Material Offshoring

3.1 Stolper-Samuelson theorem

According to Crino (2009), the reason for the outward shift of relative skilled labor demand is that industries have raised their skill intensity of production, instead of the reason that skill-intensive sectors have obtained employment shares at the expense of non skill-intensive sectors. Thus, this shift has to be explained using factors that act in the same industry. This finding has objected the Stolper-Samuelson theorem in that inter-sector (industry) trade works if each economy specializes in its stronger (more abundant) sector; for instance, developed economies specialize in skill-intensive goods; while harms locally scarce factor (low-skilled goods in developed economies) regardless of industry.

Firstly, I explain Stolper-Samuelson theorem. Chipman (1969) states that the main message from Stolper-Samuelson theorem conducts that an increase in the price of a commodity will bring about a more than proportionate increase in the price of the corresponding "intensive" factor. For example, assuming an economy with two factors and two commodities. Machine is capital-intensive and cloth is labor-intensive. The price of each commodity equals its marginal cost. So the price can be presented as:

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Pm=Km*R+W*Lm (1)

PC=KC*R+W*LC （2）

Where Km is the capital needed for machine and R is the rent; Lm is the labor needed for machine and W is the wage (note that there is perfect mobility between sectors but not countries, so the rent and wage are the same across sectors). Kc is the capital needed for cloth and Lc is the labor needed for cloth; R is the rent and W is the wage.

What happens is that machine experiences a rise in its price. Then in order for equation (1) to hold true, one of the factors has to increase as well. As assumed by the theorem, the economy is at its full employment capacity, thus change of price doesn’t change the amount of labor in either sector. The amount of land resource cannot be changed in the short-run. The factor that is most likely to rise is the rent of capital, which is more intensively used in machine manufacturing. With the rise of rent, wage must decrease in order for equation (2) to hold true. Then the fall of wage balances equation (1) in the way that, if, the fall of wage is as severe as the rise of rent, the price of machine doesn’t change. Therefore, for the price of machine to increase, the increase of rent must be more than proportional to the increase of the price of machine. To put it in a wage and skilled- unskilled labor context, this theorem shows that if the price of skill intensive product increases, then there will be more demand overall for skilled labor and the wage of skilled- labor must increase more than proportional to balance the equation.

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concerns export (say software) and import (say textile) industries with high-skilled labor and low-high-skilled labor, cooperating with the assumption of perfect inter-sector mobility of labor. Moving from autarky to free trade, price of software increases, leading to higher demand for high-skilled labor in the export industry. With the same situation in import sector, opening import leads to decrease of the price of textile. The firms in this industry shrink in production and layoff more low-skilled workers. Thus in this economy, the overall effect are the shortage of high-skilled labor and surplus of low-skilled labor. This is described by Stolper-Samuelson theorem as: Free trade benefits the factor of production that is relatively abundant regardless of industry, and harms the locally scare factor regardless of industry. The graph below is an illustration of how the labor demand changes when moving into a free trade economy from an autarky.

SS and TT are the initial equilibrium isoquants of software and textiles. (S/U)s and (S/U)t are the initial ratio of skilled to unskilled labor employed in software

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and textiles. (Wu/Ws) is the negative of the economy’s initial relative-wage ratio.

After opening up, the international price of software has risen while that of textile has dropped. Thus software production increases and textile production decreases, which is shown as a shift in the textile isoquant to T’T’. The new relative-wage ratio now is (Wu/Ws)’, which shows that the wage of skilled labor has increased relative to that of unskilled labor. (S/U)s’ and (S/U)t’ are the new ratios of skilled labor to unskilled labor employed in software and textiles industry.

3.2 Vindications against Stolper-Samuelson theorem

Crino (2009) disagreed with Stolper and Samuelson by arguing that the outward shift of skilled-labor demand has happened within industry instead of across or irrelevant to industries, because industries have raised their skill intensity of production without cutting down the employment in the

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unskilled-labor intensive industries. His argument is supported by Bernard and Jensen (1997), who state that, by the analysis of plant level evidence on the increase for skilled-labor force in the United States manufacturing during the 1980s, increases in employment at exporting plants (within skill-intensive industry, such as export industry in the US) contribute heavily to the observed increase in relative demand for skilled labor in manufacturing during the period. The factor that acts within industry to explain for the skilled- labor demand shift they find is ‘technology’. Bernard and Jensen use data from the Census Bureau’s Annual Survey of Manufactures (ASM) for the period 1976 to 1987 to investigate the relationship between exporting and labor market structure. The classifications of workers reported in the ASM are non-production and production, which non-production workers are associated with high-skilled workers and production worker are associated with low-skilled workers. They report the changes in the employment for non- production workers during the two periods 1973-1979 and 1979-1987 for four-digit industries and find that in the former period, the share of non-production workers rose at a rate of 0.320% per year, while in the latter period, this ratio increased annually at 0.546% per year. They consider the movements of the between and within components of the employment share for non-production workers and the wage share for the same workers in order to understand the reasons for these changes. Over time, they find that for the employment share, the largest increase was due to a rise in within industry shares of non-production workers, with the annual growth rates jumping from 0.199 to 0.362 while the growth rate of the between component rose from 0.121 to 0.184.

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skilled-labor demand is at the expense of unskilled- skilled-labor demand. Instead, Bernard and Jensen run a regression of plant level changes in employment on changes in technology deepening for the periods of 1973-1979 and 1979-1987 to verify their hypothesis of whether technology differences in export (skilled-labor intensive) and non-export (unskilled-labor intensive) sectors contribute to the skilled- labor demand shift. The data they use to investigate technology have three sources: the Census of Manufactures which contains information on computer investment at the plant level in 1977, 1982, and 1987; survey of industrial research and development conducted for the NSF by the Census covering about 10,000 firms in 1987 and gives data both on R&D expenditures and on scientists and engineers employed in R&D; and the Survey of Manufacturing Technology (SMT) in 1988, which asks about the plant level adoption of 17 technologies in five technology groups. The sampling frame consisted of 10,526 firms with 20 or more employees in two-digit SIC industries (major industry sectors of standard industry classification: fabricated metal products, industrial machinery & equipment, electronic & other electric equipment, transportation equipment, and instruments & related products).

However, they state that none of these three sources’ data are an exact match for technology intensity at the plant level, especially with computer investment. This is because computers differ in their skill complementarity from other forms of capital and the sources’ responses on computer investment are imputed. The computer numbers are single year flows rather than stocks of computer equipment. Moreover, the R&D data are a percentage of total R&D expenses including capital expenditures and employer salaries. In addition, sample selection is biased for the reason that the samples in the regression are larger

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than typical firms thus not representative in the industry mix. Their formulation of the regression is as follow:

Δ𝑆h𝑎𝑟𝑒_𝑖 = 𝛼 _𝑗+ 𝛽 1Δ𝑇𝑒𝑐h_𝑖 + 𝛽 2Δ𝑆𝑎𝑙𝑒𝑠 _𝑖+ 𝛽 3𝑃𝑙𝑎𝑛𝑡 𝐶h𝑎𝑟𝑎𝑐𝑡𝑒𝑟𝑖𝑠𝑡𝑖𝑐𝑠 _𝑖 + 𝜀 _𝑖

Where i indicates the exporting plant, j is the five-digit SIC industry.

ΔSharei is the annual percentage contribution of the exporting plant to the

change in the employment share in these industries of the whole labor force. Δ𝑇𝑒𝑐h _𝑖 is the technology variable consists of changes in the firm’s R&D expenditure and computer investment to total sales ratio (with the R&D expenditure as the only measure for the technology variable for the data limitation in the early period). Control variables are five-digit industry dummies, and the change in total sales, the size of the plant and the age of the plant as plant characteristics. The reason for the classification of exporting industry as skilled-labor intensive and non-exporting industry as unskilled-labor intensive is that, from the 1987 Census of Manufactures data set, they find computer investment per plant at exporting firms is more than four times higher and computer investment for per employee is 4% higher than that at non- exporting firms; R&D expenditures at exporting firms are 4.45% while only 2.34% of total sales at non- exporting firms; and Exporting firms report higher numbers of technologies employed--3.91 per plant—than the 2.20 technologies at non-exporting firms on average. The results for 1973-1979 shows that changes in Technology are positively related to the rise in the share and significant, with the R2 being high meaning that there is great

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employment ratio change. Meanwhile the 1979-1987’s regression shows a difference in the changes in Technology for being both significant and positive, whose R2 is even high. Furthermore, the increase of skilled labors employment is strongly positively related to increases in both domestic and foreign demand as shown in the increasing sales. The technology variable indicates changes in computer investment/sales and R&D/sales are significant and positive on the employment contribution in exporting firms. Other variables remain more or less steady and plant size and plant age dummies as plant characteristics are insignificant.

These results provide us with the insight that technology variable has a significant and positive effect on the change in the employment shares in exporting industries of the whole labor force. Technology investment is associated with a change in the skill mix of the workforce, and the regression confirms an intensive role of technology in the form of R&D and computer investment present. Employment shifts are largely determined by export related demand movements.

Therefore, there is an increase in the within industry shares of skilled-labor

and the reason for this increase is not as stated as Stolper-Samuelson that the share of unskilled-labor decreases, but the technology increase in the export (skilled-labor intensive) sector.

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4. Conclusion and possible further research directions

In this paper, I have explained offshoring and material offshoring in specific. To answer the research question--Has material offshoring resulted in raising skilled-labor demand while cutting down unskilled-skilled-labor demand in all sectors? -- I turned to Stolper-Samuelson theorem. It is mentioned by Crino in 2009 for its contradictory prediction against the empirical researches. The theorem indicates that, mathematically, an increase of the price of a commodity will bring about a more than proportionate increase in the price of the corresponding ‘intensive’ factor; moreover, free trade benefits the factor of production that is relatively abundant regardless of industry, and harms the locally scarce factor regardless of industry. However, Crino argues that the outward shift of skilled-labor demand (as the factor of production in the theorem) has happened within industry instead of across or irrelevant to industries, because industries have raised their skill intensity of production without cutting down the employment in the unskilled-labor intensive industries. Indeed this argument is supported by Bernard and Jensen in their 1997 paper, stating that increases in employment at exporting plants (skill-intensive) contribute heavily to the observed increase in relative demand for skilled labor in manufacturing during the period of 1980s, with the factor ‘technology’ that acts within industry to explain for the skilled-labor demand shift.

Thus, according to empirical researches, during the 1980s, the reason that there is an increase in the within industry shares of skilled- labor is not as predicted as Stolper-Samuelson theorem that the share of unskilled- labor decreases, but the technology increase in the export (skilled-labor intensive) sector.

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Further researches can incorporate the effects of the multinational enterprises’ activities. The reason that this paper doesn’t discuss about these effects is that they are not essentially related to offshoring. MNE activities aim to serve local markets in the foreign countries, rather than to serve the offshoring-initiating

home country. Nevertheless, the effects of MNE activities may have strong impacts on domestic labor markets, for the reason that as soon as a MNE has established a branch plant abroad, it is possible for the parent plant to shift employment to the branch plant if there is a relative decline is foreign wages to exploit.

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