The maid, the clerk, the doctor & their computer: globalization

 This article is written together with Eduardo Giménez, Professor of Economics at the University of Vigo. It is the first part out of four, which will be published in this blog. The full article will be published in the book "Automatization" , which will be published by the European Liberal Forum at the end of the year.

Offshoring

The development of information and communications technologies has resulted in a drastic reduction in both costs of processing information and transmitting it between two any point on the globe. The production processes do not necessarily have to be organized locally any more. Now, the possibility of vertical integration is opened at a planetary scale. This means that the various tasks of a production process can be located in distant parts of the globe. This process is known as offshoring.

Of course, this process of offshoring has a significant impact on international trade. In particular, trade in intermediate products is gradually becoming increasingly important relative to traditional trade in final products; much of the recent surge of international trade comes from middle- and low-countries; and prices of manufactured imports by developed countries from developing countries are dramatically declining. Baldwin (2011) argues that we are witnessing since the late eighties to a second type of globalization characterized by what he called connective technologies, which are enabling a drastic reduction in the cost of transmitting information (thus facilitating access to knowledge and global connection of people and companies), while the previous stage of globalization was driven by a sharp reduction in transport costs and political barriers to trade.

Figure 1

Source: Baldwin (2011).

As Blinder and Krueger (2013) have argued, essentially any job that does not need to be done in person (i.e., face-to-face) can ultimately be offshored, regardless of whether its primary tasks are abstract, routine, or manual. With this possibility in mind, it is not surprising that offshoring –being possible thank to the information and communications technologies- is affecting differently to the three characters of our story. The doctor and the maid perform tasks that cannot be offshored, not yet at least, while the tasks of the clerk are increasingly being offshored. Therefore, offshoring is also contributing to alter the relative demand of the different kinds of workers and, consequently, is affecting their relative wages. 

Occupations threatened by the computer replacement and those under the threat of relocation are not exactly the same. However, in general, it can be asserted that many occupations performed by middle-skill workers –workers with high-school or some college education- are currently confronting both threats. Autor and Acemoglu (2011) report that (i) offshorability is highest in clerical and sales occupations which imply a high degree of routine tasks; (ii) offshorability is also high in professional, managerial and technical occupations, which imply a high degree of non-routine tasks, and (iii offshorability is relatively low in production and operative occupations and even lower in service occupations. The measures of offshorability reported by Acemoglu and Autor are roughly consistent with the measures reported by Blinder and Krueger (2013). However, it must be pointed out that there is a large heterogenity into the category "production and operative occupations". According to the estimates provided by Blinder and Krueger (2013), farming, fishing and forestry occupations, construction and extraction occupations, installation, maintenance and repair occupations, and transporting and material moving occupations have a very low degree of offshorability, but other production occupations have a very high degree of offshorability. In particular, according to their best measure, 80% of jobs in other production occupations are offshorable. Offshorability is also very high in office and administrative support occupations, 41% of job in these occupations are offshorables according to the best measure reported by Blinder and Krueger. Offshorability is also high in sales and related occupations (17.8%), professional and related occupations (20.5%), and managment, business, and financial occupations (16.4%). However, the percentage of offshorable jobs in service occupation is only 0.7%. Blinder and Krueger (2013) estimate that roughly 25% of U.S jobs are offshorable. The fith column of Table 1 displays a measure of offshorability of several occupations in 16 European countries elaborated by Goos et al. (2010) (a higher number means higher offshorability).

Table 1

Source: Goos, Maning and Salomons (2010)

Autor, Dorn and Hanson (2015) reports that the U.S. local labor markets whose initial industry composition exposes them to rising Chinese import competition experience significant falls in employment, particularly in manufacturing and among non-college workers. Ebenstein et al. (2009) present evidence that globalization has put downward pressure on worker wages through the  reallocation of workers away  from higher  wage manufacturing jobs into other sectors and other  occupations. Using a panel of  workers, they find that occupation switching due to  trade led to  real wage losses of 12 to 17 percentage points.

Superstars

So far, our history has been about ordinary workers. Maids, clerks, doctors,...we can find thousands. However, a small number of workers are out of the norm. They are superstars (see Rosen (1981)), as the soccer players Leo Messi or Slatan Ibrahimovic. In recent decades, there has been an impressive burst of earnings of this so-special type of workers.

The income share of the top 1% of income distribution has soared since the late eighties (see Figure 2). At this stage of XXI century in countries like the United States or Britain, the top 1% income share is hovering at the figures observed at the beginning of the past century (see Atkinson, Piketty and Saez (2011)). In fact, much of the increase in inequality in income distribution in many developed countries is explained by the increase in the top 1% (see Bell and Van Reenen (2010)). Keep in mind the shocking remunerations for the most CEOs of large companies (see Figure 3). Before the eighties, their earnings were certainly enviable, but did not reach, not even by far, the stratospheric current figures (see Frydman and Jenter (2010)). Gabaix and Landier (2006) give an explanation of the increase in CEO earnings based on the ideas developed below.

Figure 2

Source: Van Reenen (2010). Top 1% share of all income in English speaking countries.

Figure 3

Source: Frydman and Jenter (2010). Data for the United States.

To understand the relationship between the earnings of the superstars and technical change, consider Luis Suárez, footballer of F.C. Barcelona in the fifties, and Luis Suárez, currently footballer of F.C. Barcelona.[1]  In the fifties and sixties, Suárez I, as Suárez II today, produced non-rival goods –shots, dribbling, passing, goals,...- which could be enjoyed by a lot of people at the same time. People paid to see the exploits of Suárez I on the pitch, and now pay for Suárez II’s goals. Suárez I, as Suárez II today, earned a lot of money because a lot of people watched and admired his gaming.  However, in the fifties, when Suárez I played soccer, technology only allowed a hundred thousand people to watch Suárez I’s gaming: those people who attended every Sunday to Camp Nou Stadium. Nowadays, millions of people around the globe watch the goals of Suárez II every week on their televisions and millions more may dream of being Suárez II playing on their gaming consoles. More people can currently enjoy Suárez II’s gaming than Suárez I’s in the fifties and sixties thanks to the information and communications technologies.  Accordingly, Suárez II’s earnings are much higher than Suárez I ever dreamed.

Moreover, the difference between Suárez II’s earnings and most players in the Spanish soccer league is greater than the difference between Súarez I’s earnings and most players in the Spanish league at those days. In the fifties, football-mad people of Vigo had to attend Balaídos Stadium to watch R.C. Celta de Vigo matches because they could not see to play Suárez I every week. They paid their tickets, as the supporters of F.C Barcelona did to attend Camp Nou Stadium. In the fifties, Barcelona soccer players earned more money than Celta soccer players because more people went to watch them, but, not much more. Nowadays, people from Vigo do not need to attend Balaídos Stadium to watch soccer. They can watch F.C. Barcelona matches using the pay-perview digital television services and, consequently, Barcelona soccer players earn much more money than their colleagues of R. C. Celta. This increase in earning differences is a consequence from that, when people produce non-rival goods, the winner takes all. In the example, watching soccer in the stadium is not the same as watching soccer on TV, watching your team is not the same as watching any other team,…There are several reasons because R.C. Celta and F.C Barcelona are not perfect substitutes, so that the core idea “winner takes all” does not work perfectly.

In short, the development of the information and communications technologies is increasing the degree of non-rivalry of some goods produced by some economic agents, which allows them to earn a lot of money if they are the winners of a “winner-take-all” race. This means that globalization driven by the information and communications technologies has played an important role in boosting demand for the services of some superstar workers, which has increased their earnings and income inequality.

References

Acemoglu, D., & Autor, D. H. (2011). Skills, tasks and technologies: Implications for employment and earnings. Handbook of Labor Economics, 4, 1043-1171.

Atkinson, A. B., Piketty, T., & Saez, E. (2011). Top incomes in the long run of History. Journal of Economic Literature, 49(1), 3-71.

Autor, D. H., Dorn, D., & Hanson, G. H. (2015). Untangling trade and technology: Evidence from local labour markets. The Economic Journal, 125(584), 621-646.

Baldwin, R. (2011). Trade and industrialisation after globalisation's 2nd unbundling: How building and joining a supply chain are different and why it matters. NBER Working Paper 17716.

Bell, B., & Van Reenen, J. (2010). Bankers’ bonuses and extreme wage inequality in the UK. Centre for Economic Performance Special Report Nº 21.

Blinder, A., & Krueger, A. B. (2013). Measuring offshorability: A survey approach. Journal of Labor Economics, 31(S1), S97-S128. 

Ebenstein, A., Harrison, A., McMillan, M. and S. Phillips (2009). Estimating the impact of trade and ofshoring on American workers using the current populations surveys. NBER Working Paper 15107.

Frydman, C., & Jenter, D. (2010). CEO Compensation. Annual Review of Financial Economics, 2(1), 75-102.

Gabaix, X. and Landier, A. (2006). Why has CEO pay increased so much? NBER Working Paper 12365.

Goos, M., Manning, A., & Salomons, A. (2010). Explaining job polarization in Europe: the roles of technology, globalization and institutions. CEP Discussion Paper Nº 1026, LSE.

Rosen, S. (1981). The economics of superstars. The American Economic Review, 71(5), 845-858.

Van Reenen, J. (2011). Wage inequality, technology and trade: 21st century evidence. Labour Economics, 18(6), 730-741.

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[1] The supporters of Deportivo de La Coruña -hometown of Suarez- had the opportunity to enjoy the Suárez’s gaming prior to his passage by F.C. Barcelona. Afterward, Luis Suárez won two European Cups with Inter of Milan. Luis Suarez is the only Spanish soccer player (Galician, more precisely) winning a Golden Ball. The homonymous Uruguayan player who currently plays in the ranks of F.C Barcelona was so named in his honor.

The maid, the clerk, the doctor & their computer: contrasting fortunes

Fernando del Río and Eduardo Giménez

This article is the first part out of four, which will be published in this blog. These fourth parts are preliminary versions of a work which will be included as a chapter of the book "Automation", which will be  published by the European Liberal Forum at the end of the year.

At the end of the eighties the British film director, Peter Greenaway, wrote and directed his more successful film entitled “The Cook, the Thief, His Wife & Her Lover”. Greenaway narrates the intertwined stories of the four characters referred in the title of his film.

Along these lines, we also aim to tell the vicissitudes of four characters. Those four mentioned in the title. Three are of flesh and blood, the other the outcome of human ingenuity. As we shall see, the fate of the first three is closely linked to the evolution of the latter.  Let us say you that the maid is the alter ego of low-skilled, low-wage workers, the clerk of middle-skill, middle-wage workers, and the doctor of high-skill, high-wage workers. The computer represents the role of the information and communication technologies (ICT), which have changed our lives in the last decades.

We must poke our nose into their lives for a relatively short period of time. Otherwise, we would risk going on too long. We think that the last twenty five years will be enough. Since the late eighties –actually, the time of the premiere of Greenaway’s film- until today. In addition, we wish to announce that it is not our intention to bore you with data. There are quite a lot of them. If you are interested in to take a look on them, the academic papers by Acemoglu and Autor (2011) and Van Reenen (2011) and the bibliographic references given along this storytelling can provide you a broad data array. Do not think that the experiences of our characters are constraint to a particular country. You can place their adventures in the United States or Europe. Even, if desired, in Australia or Canada. Their stories are very similar in any developed country. I will not say identical, but similar, at least broadly.

Perhaps every child comes with a loaf under his arm, but we do not even know if our first three characters must be grateful for their computer. The rise and development of the information and communications technologies has brought mixed fortunes for them. The doctor has taken advantage from them. The computer complements her work and makes her more productive. However, the computer does not seem to have done some good for the maid, while the clerk had to see how many of her tasks are now undertaken by the computer or were relocated to faraway places, which, thanks to the information and communications technologies, are not so much anymore.

Job polarization

The job opportunities of our three characters have changed differently from the end of the eighties. The job opportunities for the maid and the doctor have increased, while the clerk has been left with fewer job opportunities. This means that, in the past 25 years, the job distribution -just as the wage distribution- has undergone an ongoing process of polarization: both the share of employment in high-skill, high-wage occupations and low-skill, low-wage occupations increased. It must be pointed out that, in the nineties, relative employment growth was rapid in high-skill, high-wage occupations and modestly positive at low-skill, low-wage occupations, but it was heavily concentrated among the low-skill, low-wages occupations over the intervening years of this century. However, the behavior of employment was different during the eighties. In this decade, employment growth by occupation was nearly monotonic in occupational skill: occupations below the median skill declined as a share of employment and occupations above the median increased.

 Figure 1 displays the empirical evidence on job polarization reported by Acemoglu and Autor (2010) for the United States (see also Autor et al. (2006)). As reported by Goos, Manning and Salomons (2009, 2010), job polarization also happened in Europe. Table 1 displays the empirical evidence on job polarization for the average of 16 European countries and Table 2 dispplays the empirical evidence for the sixteen countries.  Figure 2 provides a comparison between Europe and the United States

Figure 1. Changes in U.S. employment

Source: Acemoglu and Autor (2011). Data for the United States.

Figure 2: Changes in employment Europe and United States

 Source: Acemoglu and Autor (2011).

Table 1: Changes in hours worked for occupations ranked by their mean 1993 European wage

Source: Gooss, Maning and Salomons (2009)

Table 2: Changes in hours worked for high-, middling- and low-paying occupations in 16 European countries

Source: Goos, Maning and Salomons (2009)

         Wage inequality

        There is a strong empirical evidence that since the late 1970s and continuing through the mid-2000s, overall wage inequality has been increasing in the United States (see Autor et al. (2008) and Lemieux (2006)) and United Kingdom (Machin and Van Reenen (2008)). 

        In particular, wage inequality rose between the middle of the seventies and the end of the eighties. During this period, the wage structure changed monotonically: the upper percentiles of the wage distribution grew much more than the median and the lower percentiles grew less than the median (see Figure 3 and Table 3). That is to say, the doctor’s wage grew much more than the clerk’s wage, while the latter grew more than the maid’s wage.

           However, the wage fate of the maid, the clerk and the doctor has been different in the last 25 years. In particular, in the United States, the maid’s wage grew more than the wage of the clerk and the doctor’s wage grew much more than the wages of the clerk and the maid. This means that, in the last 25 years, wage distribution undergone a process of polarization: the upper percentiles grew much more than the median and the lower percentiles grew more than the median (see Figure 3). In the United Kingdom, wage polarization also happened, but more slightly (see Table 3). Green and Sand (2015) report that, in Canada from 1971 to 2005, the wage pattern reflects a simple increase in inequality with greater growth in high paid than middle paid occupations and greater growth in middle than low paid occupations. Since 2005, they report that there has been some wage polarization but this is present only in some parts of the country and seems to be related more to the resource boom than technological change (see Figure 4).

 Figure 3: Changes in wages in the United States 

Source: Acemoglu and Autor (2011). Data for the United States.

 Figure 4: Changes of real wages in Canada

Source: Green and Sands (2015)

Table 3: Wage evolution in UK

Solurce: Machin and Van Reenen (2007)

There is less systematic evidence for the evolution of the wage distribution outside of the US and UK, especially for more recent years. Broadly speaking the 1980s rise in inequality was seen only in the United Kingdom, United States and some Anglophone countries as Canada or Australia (see Atkinson and Leigh (2007)). Things are a little different after the nineties. Wage structures were stable in Continental European countries, but there is evidence of widening wage structures starting to occur after the middle of the nineties in places previously characterized by stable wage structures. In particular, Dustman et al. (2009) find that, in Germany, the wages of workers in lower percentiles of the wage distribution fell since the middle of the nineties, while the wages of the upper centiles increased more than the median (see also Antonczyck et al. (2010)) . Therefore, wage inequality increased at the top in the United States in the last 25 years, while it increased at the top and at the bottom in Germany after mid-90s (see Figure 5). 

Figure 5: Wage growth in Germany

Dustman et al. (2009)

The Continental European countries did have a larger increase in unemployment which may be due to the same underlying forces that have pushed up wage inequality in Britain and America. Differences in institutions or in tastes and social norms might explain different cross-country patterns of change. In particular, the differences between Continental European countries and the United States and United Kingdom. The basic idea is that, in more flexible labor markets, technological shocks result in an adjustment through prices, while, in more rigid labor markets, adjustment is made through quantities. Therefore, in Continental European Countries, the maid and the clerk have not seen to increase their wage difference relative to the doctor, but at the expense of a higher risk of unemployment (see Figure 6, which compares evolution of unemployment in France and the United States).

Figure 6: Unemployment in France and United States

Source: Eurostat.

 In the next installment, the reasons for the contrasting fortunes of our characters will be addressed.

References

Acemoglu, D., & Autor, D. H. (2011). Skills, tasks and technologies: Implications for employment and earnings. Handbook of Labor Economics, 4, 1043-1171.

Antonczyk,  D., DeLeire, T., & Fitzenberger, B. (2010). Polarization and rising wage inequality: comparing the US and Germany. ZEW-Centre for European Economic Research Discussion Paper, (10-015).

Atkinson, A. and Leigh, A. (2007). The Distribution of Top Incomes in Australia. The Economic Record, 83(262), 247–261.

Autor, D. H., & Dorn, D. (2010). Inequality and specialization: the growth of low-skill service jobs in the United States. MIT Working Paper.

Autor, D., L. Katz, and M. Kearney (2006). The polarization of the US labor market.  American Economic Review, 96, 189-194.

       Autor, D., Katz, L., and Kearney, M. (2008). Trends in U.S. Wage Inequality: Re-Assessing the Revisionists.  Review of Economics and Statistics, 90(2):300–323.

     Dustmann, C., Ludsteck, J., and Sch¨onberg, U. (2009). ”Revisiting the German Wage Structure”. The Quarterly Journal of Economics, 124(2), 843–881.

Goos, M., Manning, A., & Salomons, A. (2009). Job Polarization in Europe. The American Economic Review, Papers and Proceedings, 99(2), 58-63

Goos, M., Manning, A., & Salomons, A. (2010). Explaining job polarization in Europe: the roles of technology, globalization and institutions. CEP Discussion Paper Nº 1026, LSE.

Green D. A. and B. M. Sand (2015). Has the Canadian Labor Market Polarized?. Canadian Journal of Economics, 48(2), 612-646.

Lemieux, T. (2006). Increased Residual Wage Inequality: Composition Effects, Noisy Data, or Rising Demand for Skill. American Economic Review, 96, 461–498.

Machin, S. and Van Reenen, J. (2007). Changes in Wage Inequality. Centre for Economic Performance, Special Paper Nº18.

Van Reenen, J. (2011). Wage inequality, technology and trade: 21st century evidence. Labour Economics, 18(6), 730-741.