Broadband, Firms and Employment

6.7.1 Broadband and job creation

Broadband contribution to employment can be estimated both in terms of the direct impact resulting from network deployment (e.g. construction effect) and in terms of the indirect positive externalities derived from additional network coverage (e.g. network externalities). Each type of effect is comprised of three specific impacts (see table 6.35).

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TABLE 6.35

Impact of Broadband on Employment

The following section will review the research conducted to date in assessing each type of effect. In addition, the section will present evidence of these specific effects in the context of developing nations. 

• 6.7.1.1 Job creation through network construction

  Broadband network construction affects employment in three ways. In the first place, network construction requires the creation of direct jobs (such as telecommunications technicians, construction workers, and manufacturers of the required telecommunications equipment) to build the wireline and wireless network facilities. In addition, the deployment of broadband networks has an impact on indirect employment triggered by upstream buying of inputs required for broadband network construction (which creates employment in, for example, metal and electrical equipment manufacturing sectors). Finally, the household spending based on the income generated from the direct and indirect jobs created by network deployment induces employment throughout the economy.

  Input-output tables help calculating the direct, indirect, and induced effects of broadband network construction on employment. The interrelationship of these three effects can be measured through multipliers, which estimate how one unit change on the input side (e.g. investment in network deployment) affects total employment change throughout the economy.

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  FIGURE 6.39

  Structure of Input-output table

  Source: Adapted from Katz (2008b)

  According to input-output economics, multipliers are of two types. Type I multipliers measure the direct and indirect effects (direct plus indirect divided by the direct effect), while Type II multipliers measure Type I effects plus induced effects (direct plus indirect plus induced divided by the direct effect).

  Six national studies have estimated the impact of network construction on job creation: Crandall et al. (2003), Katz et al. (2008b), Atkinson et al. (2009), Liebenau et al. (2009), Katz et al. (2009), and Katz et al. (2010). They all relied on input-output matrices and assumed a given amount of capital investment:

  • United States: US $ 63 billion needed to reach ubiquitous broadband service in this country (Crandall et al., 2003)
  • Switzerland: CHF 13 billion to build a national multi-fiber network for Switzerland (Katz et al. (2008b)
  • United States: US $ 10 billion invested in broadband as a counter-cyclical stimulus (Atkinson et al. (2009)
  • United States: US$ 6.4 billion invested in broadband as part of the Recovery Act voted by the US Congress in 2009 (Katz et al., 2009)
  • United Kingdom: US $ 7.5 billion for needed to complete broadband deployment in the United Kingdom (Liebenau et al. (2009)
  • Germany: 35.4 billion Euros to implement Germany’s National Broadband Strategy as well as an Ultra-broadband Scenario targeted for 2020 (Katz et al., 2010)

  Each study will be reviewed in turn.

  In 2003 Crandall et al. relied on the multiplier effects calculated by the Bureau of Economic Analysis, and concluded that US $63.6 billion of capital expenditures in broadband in the United States would trigger the creation of 61,000 jobs per annum. In addition, if investments were assigned to more advanced broadband platforms (such as VDSL, or FTTx), the cumulative effect of current and new generation of broadband would result in an increase of 140,000 new jobs per year. By adding both effects, the authors concluded that universal broadband adoption would trigger the creation of 1.2 million jobs, (546,000 in network deployment and 665,000 generated in upstream industries.)

  In a similar vein, a study by Katz et al. (2008) estimated the impact of the deployment of a national FTTH network in Switzerland at a cost of CHF 13 Billion. Using national input-output tables from Eurostat, the authors estimated that deployment of such a network could generate 114,000 jobs, 83,000 in direct and 31,000 in indirect employment. The study did not estimate induced employment.

  Atkinson et al. (2009) also relied on input-output tables from the US Bureau of Economic Analysis to assess the employment impact of a $ 10 Billion investment in broadband infrastructure aimed at tackling the 2008 economic crisis. Their conclusion was that such an investment could create 64,000 direct jobs and 166,000 indirect and induced jobs.

  year period from network construction. According to the analysis, the investment of $6.390 billion  *  An estimate of funds dedicated primarily to broadband deployment, as opposed to ancillary activities such as broadband mapping. would generate 37,300 direct jobs over the course of the stimulus program (estimated to be four years). In addition, based on a Type I employment multiplier of 1.83, the bill could generate 31,000 indirect jobs. The split across sectors is presented in table 6.36.

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  TABLE 6.36

  United States: Type I employment effects of Broadband Stimulus Bill

  Source: Adapted from Katz et al. (2009a)

  Once the Type I employment was calculated, the Type II effect was estimated. As mentioned above, the Type II effect refers to employment generated as a result of household spending derived from the Type I one. In this case, the Type II multiplier (direct + indirect + induced jobs/direct jobs) was 3.42. The combination of direct (37,300), indirect (31,000) and induced jobs (59,500) yielded a total employment impact of 127,800 jobs over a four-year period. The average annual employment generation effect was estimated at 31,950 jobs per year.

  The investment multipliers for the United States broadband investment has been fairly consistent across research studies (see table 6.37).

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  TABLE 6.37

  United States: Comparative Investment Multipliers

  Source: Adapted from Katz et al. (2009a)

  In other words, all three studies conducted to assess the employment contribution of a broadband construction program in the United States coincided in the magnitude of job creation. Differences only remained in the amount of capital to be invested.

  In a similar approach to the US studies, Liebenau et al. (2009) calculated the labor impact of implementing the "Digital Britain Plan” in the United Kingdom. According to this study, the investment required to implement such a program would be US $ 7.5 billion, which could generate 211,000 jobs (comprising 76,500 direct and 134,500 indirect and induced).

  Finally, Katz et al. (2010) estimated the employment impact of fulfilling the broadband deployment targets of Germany’s National Broadband Strategy and an assumed Ultra-broadband Plan to be implemented by 2020. The estimated 35 billion Euros would generate 304,000 jobs over five years. The primary sector benefited in terms of job creation would be construction with 125,000, followed by telecommunications (28,400) and electronics equipment manufacturing (4,700). Total indirect jobs generated by sector interrelationships measured in the input/output matrix would be 71,000. The key sectors benefited from the indirect effects are distribution (10,700), other services (17,000) and metal products (3,200). Finally, household spending generated directly and indirectly, will result in 75,000 induced jobs. Based on these estimates, the Type I multiplier for employment would be 1.45 while the Type II would be 1.92.

  Additionally, the implementation of the expected ultra-broadband evolution would generate 237,000 incremental jobs between 2015 and 2020. Similar to the breakdown reviewed above, this figure would comprise 123,000 in direct jobs, 55,000 indirect jobs and 59,000 in induced jobs.

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  TABLE 6.38

  Germany: Total Employment Impact of Broadband Network Construction

  Source: Katz et al. (2010)

  As in the other studies, the German case concluded that the labor intensive nature of broadband deployment determines that the construction jobs to be created are significant and, despite the high technology nature of the ultimate product, broadband is to be seen as economically meaningful as conventional infrastructure investment such as roads and bridges.

  To summarize, all studies that have relied on input-output analysis have calculated multipliers, which measure the total employment change throughout the economy resulting from the deployment of a broadband network. Beyond network construction (direct employment), broadband construction has two additional employment effects. Network deployment will result in indirect job creation (incremental employment generated by businesses selling to the sectors that are directly involved in network construction) and induced job creation (additional employment induced by household spending of the income earned from the direct and indirect effects) (see table 6.39).

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  TABLE 6.39

  Broadband Construction Impact on Job Creation

  Source: Compiled by the author

  Cognizant that multipliers from one geographic region cannot be applied to another, it is useful to observe the summary results for the multipliers of the four input-output studies. 

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  TABLE 6.40

  Employment Multiplier Effects of Studies Relying on Input-Output Analysis

  Source: Adapted from Katz (2009a)

   

  Note: Crandall et al. (2003) and Atkinson et al. (2009) do not differentiate between indirect and induced effects, therefore we cannot calculate Type I multipliers; Katz el (2008b) did not calculate Type II multiplier because induced effects were not estimated.

  As mentioned above, according to the sector interrelationships depicted above, a European economy appears to have lower indirect effects than the US. Furthermore, the decomposition also indicates that a relatively important job creation effect occurs as a result of household spending based on the income earned from the direct and indirect effects. The induced effects are very large.

  While input-output tables are reliable tools for predicting investment impact, two words of caution need to be given. First, input-output tables are static models reflecting the interrelationship between economic sectors at a certain point in time. Since those interactions may change, the matrices may lead us to overestimate or underestimate the impact of network construction. For example, if the electronic equipment industry is outsourcing jobs overseas at a fast pace, the employment impact of broadband deployment will diminish over time and part of the counter- cyclical investment will "leak" overseas. Second, it is critical to break down employment effects at the three levels estimated by the input-output table in order to gauge the true direct impact of broadband deployment. Having said that, all these effects have been codified and therefore, with the caveat of the static nature of input- output tables, we believe that the results are quite reliable.

  These studies have provided the theoretical framework and tools to estimate the overall job impact of broadband-enabled counter-cyclical programs. For example, In 2010, Australia embarked on the construction of a National Broadband Network with a total funding estimated at AUD40.9 billion over 8 years to build and operate a new open access wholesale network. The plan will support up to 25,000 jobs over the life of the project. Funding will initially come from government, which will contribute equity of AUD27.5 billion, with other funding expected to come from operational earnings and private debt. In 2015, the wholesale network provider (NBN Co) will begin raising funds through capital markets, with an estimated AUD13.4 billion expected to be needed to finance the project.

• 6.7.1.2 Broadband spillovers on business expansion and innovation

  Beyond the employment impact of network construction, researchers have also studied the impact of network externalities on job creation variously categorized as "innovation", or "network effects".* Once deployed extensively, broadband becomes a “general purpose technology” with the power to facilitate growth and innovation throughout the economy. The study of network externalities resulting from broadband penetration has led to the identification of numerous effects:

  • New and innovative applications and services, such as telemedicine, Internet search, e-commerce, online education and social networking*  
  • New forms of commerce and financial intermediation* 
  • Mass customization of products* 
  • Marketing of excess inventories and optimization of supply chains* 
  • Business revenue growth*   
  • Growth in service industries* 

  The results of microeconomic research have been utilized to estimate the impact of broadband on job creation. For example, Fornefeld et al., (2008) identified three ways that broadband impacts employment: first, the introduction of new applications and services causes acceleration of innovation in terms of creation of new ventures and natural business expansion requiring additional workers; second, the adoption of more efficient business processes enabled by broadband increases productivity, which in term, tends to reduce employment; and third, the ability to process information and provide services remotely makes it possible to attract (or loose) employment from other regions through outsourcing. According to Fornefeld et al. (2008), these three effects act simultaneously, whereby the productivity effect and potential loss of jobs due to outsourcing are neutralized by the innovation effect and gain of outsourced jobs from other regions.

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  FIGURE 6.40

  Network Effects of Broadband on Employment

  Note: This causality chain was adapted from a model originally developed by Fornefeld et al., 2008 in a report for the European Commission.

  Thus, according to the authors, the negative effect of broadband productivity is compensated by the increase in the rate of innovation and services, thereby resulting in the creation of new jobs. The third effect may induce two countervailing trends. On the one hand, a region that increases its broadband penetration can attract employment displaced from other regions by leveraging the ability to relocate functions remotely. On the other hand, by increasing broadband penetration, the same region can lose jobs by virtue of the outsourcing effect. While we are gaining a better understanding of these combined "network effects", the research is still at its initial stages of quantifying the combined impact. The study by Fornefeld et al. (2008) is probably the first attempt to build a causality chain. It applies ratios derived from micro-economic research to estimate the combined impact of all effects, rather than conducting aggregate econometric analysis of historical data.

  Most of the research regarding the impact of broadband externalities on employment has been conducted using US data. There are two types of studies of these effects: regression analyses and top down multipliers. The first ones attempt to identify the macro-economic variables that can impact employment,* while the second ones rely on top-down network effect multipliers.

  Among the econometric studies of employment impact, are Gillett et al. (2006), Crandall et al. (2007), Shideler et al. (2007) and Thompson and Garbacz (2008). Relying on standard regression analysis, a team of MIT and Carnegie Mellon researchers* conducted a study that sought to measure the impact of broadband on a number of economic indicators including employment. Initially, the study tried to estimate the relationship between broadband and employment at the state-level. However, it concluded that data at this level of aggregation did not permit observation of any measurable impact. It was only when they turned to the zip code level that a positive impact of broadband was observed: the availability of residential broadband added over 1.5% to the employment growth rate in a typical community.* 

  Crandall et al. (2007) relied on the same methodology to conduct a study focused on the effects of broadband on output and employment for the 48 US states. The conclusion of their multivariate regression analysis was that "for every one percentage point increase in broadband penetration in a state, employment is projected to increase by 0.2 to 0.3 percent a year (...) (an increase of about 300,000 jobs, assuming the economy is not already at "full employment").

  Shideler et al. (2007) analyzed the relationship between broadband saturation and employment growth in counties of the US state of Kentucky. The authors found that the coefficient on broadband saturation is positive and statistically significant on aggregate county employment in several industrial sectors (details below). It ranged from 0.14% to 5.32% for each 1% incremental broadband penetration.

  Finally, Thompson and Garbacz (2008) employed a stochastic-frontier production function to measure the direct and indirect impact of broadband penetration on the GDP of 48 US states. While they found that employment in certain industrial sectors tends to grow with broadband penetration, they also pointed that broadband deployment may cause a substitution effect between capital and labor.

  To sum up, after examining the conclusions of the regression studies, the evidence regarding broadband employment externalities appears to be quite conclusive (see table 6.41).

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  TABLE 6.41

  Research results of Broadband Impact on Employment in the United States

  Source: Compiled by the author

  According to this research, the impact of broadband on employment creation appears to be positive. However, as the data indicates, the impact on employment growth varies widely, from 0.2 % to 5.32 % for every increase in 1% of penetration. There are several explanations for this variance. As Crandall indicated, the overestimation of employment creation in his study is due to employment and migratory trends, which existed at the time and biased the sample data. In the case of Gillett et al. (2006), researchers should be careful about analyzing local effects because zip codes are small enough areas that cross-zip code commuting might throw off estimates on the effect of broadband. For example, increased wages from broadband adoption in one zip code would probably raise rent levels in neighboring zip codes prompting some migration effects. Finally, the wide range of effects in the Shideler et al. (2007) study is explained by the divergent effects among industry sectors (see below).

  Beyond regression studies, "network effect" multipliers have been used to assess the impact of broadband on job creation in a top down fashion. Within this group, key studies are Pociask (2002), Atkinson et al. (2009) and Liebenau et al. (2009). Pociask (2002) and Atkinson et al. (2009) studies relied on an estimated "network effect" multiplier, which is applied to the network construction employment estimates. For example, Pociask relied on two multiplier estimates (an IT multiplier of 1.5 to 2.0 attributed to a think tank and another multiplier of 6.7, attributed to Microsoft) and calculated an average of 4.1. Similarly, Atkinson et al. (2009) derived a multiplier of 1.17 from Crandall et al. (2003). Though the top-down approach allows estimation of the broadband impact, it does not have a strong theoretical basis. Network effects are not built on interrelationships between sectors. They refer to the impact of the technology on productivity, employment and innovation by industrial sector.

  Beyond aggregate estimates indicating positive externalities of broadband, disaggregated effects are more complex. For example, a study by Katz et al. (2010) on the broadband externalities of Germany’s National Broadband Strategy found that, while the positive effects on employment and economic output resulting from enhanced productivity, innovation and value chain decomposition are significant throughout Germany; the job impact of broadband tends to vary over time and by region. By splitting the German territory into two groups, counties with 2008 average broadband penetration of 31 % of population and counties with average broadband penetration of 24.8 %, the analysis determined that the type and pattern of network effects of broadband varies by region. In high broadband penetrated counties the short-term impact of the technology is very high both on GDP and employment, but it declines over time. This "supply shock" is believed to occur because the economy can immediately utilize the new deployed technology. Furthermore, the fact that employment and GDP grow in parallel indicates that broadband has a significant impact on innovation and business growth, thereby overcoming any employment reduction resulting from capital/labor substitution effects.

  On the other hand, in counties with low broadband penetration the impact of broadband on employment is slightly negative in the initial years. Negative initial employment growth appears to indicate that the productivity increase resulting from the introduction of new technology is the most important network effect to begin with. However, once the economy develops, the other network effects (innovation and value chain recomposition) start to play a more important role, resulting in job creation.* Therefore broadband deployment in low penetrated areas will likely generate high stable economic growth ("catch up" effect) combined capital/labor substitution, which initially limits employment growth ("productivity" effect). Figure 6.41 presents in conceptual fashion a comparison of impact in both regions.

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  FIGURE 6.41

  Conceptual view of comparative broadband regional effects

  Source: Adapted from Katz et al. (2010a)*

  The finding conceptualized in figure 6.39 is consistent with Lehr et al. (2005) and Thompson et al. (2005) finding that there is a short-term negative impact of broadband on employment due to process optimization and capital-labor substitution. However, the German evidence appears to point out that the short-term negative effect is limited to low broadband penetration geographies. These differentiated effects are critical in generating evidence regarding job creation of broadband in rural areas. The results of the research appear to be mixed in this regard.

  In the first place, in response to the argument that broadband deployment in rural areas stimulates the relocation of establishments to those areas and therefore create jobs, evidence indicates that relocation as a result of broadband tends to occur to the suburban peripheries of metropolitan areas rather than the strictly rural geographies (Katz et al., 2011). Furthermore, research also indicates that the jobs created in the periphery are jobs lost in metropolitan areas (“job cannibalization” effect), which means that no additional jobs are created. For example, Lehr et al. (2005) assessed a district-level (zip-code) panel of data on broadband deployment in the United States and concluded that zip codes with broadband experienced faster job growth rate (1% to 1.4%) between 1998 and 2002, experienced faster growth in business establishments (0.5% to 2.2%), and a favorable shift in the mix of business toward higher value-added ICT intensive sectors (0.3% to 0.6%). In response to this finding, some economists argue that, “job cannibalization” resulting from firm relocation triggered by broadband technology yields equilibrium in labor markets (and therefore has a positive contribution).

  Secondly, research indicates that job effects of broadband in rural areas are highly dependent on industrial sectors. As we will show below, job creation effect in metropolitan peripheries is present in wholesale trade and financial services, whilebroadband-induced employment growth in rural areas is only significant in retail trade, and health services.

  In sum, the employment impact of broadband by geography appears to indicate the existence of multiple effects at work (see figure 6.42).

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  FIGURE 6.42

  Geographic impact of employment triggered by broadband deployment

• 6.7.1.3 Broadband and employment in developing countries

  Beyond the studies conducted in mature economies, the aggregate impact of broadband on employment has begun to be studied in emerging countries as well. For example, Katz (2012) constructed a cross-sectional sample for the 27 Brazilian states similar to that one utilized by Katz et al (2010a) for Germany, where the dependent variable was the rate of change of unemployment: 

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  TABLE 6.42

  Brazil: Variables utilized to estimate the impact of broadband on job creation

  Source: Adapted from Katz (2010b)

  The results of the model are as follows (see table 6.43)

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  TABLE 6.43

  Brazil: Impact of broadband on job creation

  Source: Adapted from Katz (2010b)

  However, the relationship between the rate of change of unemployment rate and the rate of change in broadband penetration is significant and with the expected negative sign. According to the model results, a change of 10% in broadband penetration could reduce the unemployment rate by 0.06 percentage points. On the other hand, it is counterintuitive that the difference in schooling years and population growth are not statistically significant in explaining the differences in the level of unemployment across regions.

  The availability of an extensive database of quarterly data for Chile allowed the development of a panel of time series data for each of Chile's administrative regions. This database was constructed by compiling data for each of Chile's regions (except for the Metropolitan Region due to the lack of quarterly data) from 2001 until the fourth quarter of 2009. The dataset contains the following information: 

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  TABLE 6.44

  Chile: Variables used to estimate the broadband impact on job creation

  Source: Katz (2010)

  A model including level of economic activity and broadband penetration was specified. In addition, an alternative model was proposed aimed to study possible effects of human capital and specialization on the level of employment. According to the methodology used, other specific characteristics of each region that could have an impact on the labor market are controlled by the fixed effects of the panel data. Thus, the model results are as follows (see table 6.45).

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  TABLE 6.45

  Chile: Broadband impact on job creation

  Source: Katz (2010)

  The economic activity variable remained unaltered between the two specifications; in both cases it was significant and positive. The coefficient of broadband penetration is significant* and positive in both specifications. The small variation between the two specifications suggests that the contribution of 1 percentage point in broadband penetration would contribute nearly 0.18 percentage points to the employment rate.

  An interesting result on the second specification was the coefficient of human capital, which resulted significant at the 10% level and with a negative sign. Contreras at al (2008) argues that this result is mostly explained by the impressive increment in the years of schooling of the population in one generation and the entrance of women to the labor force.*   

  A model similar to one constructed for Germany was developed by Katz et al. 92011) for Colombia. In this case, growth of the employment rate was studied in relation to the increase in broadband access lines, controlling for population growth and economic development. The model was specified both for the whole country and for departments with high and low broadband penetration.

  Growth of employment rate (%) Dependent variable: growth of employment rate (2006-10) Independent variables: growth in broadband connections (2006-2010), population growth (2006-2010), GDP 2003
  	Total	Low penetration	High penetration
  Growth in broadband connections (%)	0.0003*	0.003*	0.0006572
  	(0.0001359)	(0.0001547)	(0.0005495)
  Population growth (2006-10) (%)	0.0160	-0.2539	0.5937073*
  	(0.5114836)	(0.7899623)	(0.3761862)
  GDP 2003 (in million pesos)	0.0053	-0.1085	0.0003309
  	(0.0077051)	(0.1308956)	(0.0090124)
  R^2 adjusted	0.0110	0.0318	0.0338
  Prob>F	0.0730	0.0321	0.4351
  Number of observations	132	64	68

  TABLE 6.46

  Colombia: Impact of increase in broadband penetration on job creation

  Source: Katz & Callorda (2011)

   

  Note: Low penetration departments refers to administrative districts whose broadband penetration is lower than the country mean, while high penetration refers to departments whose broadband penetration is higher than the country mean.

  In these models, the broadband contribution to job creation is significant at the national level and for the low penetrated departments; in the highly penetrated departments, statistical significance is only 24%. On the other hand, population growth appears to have an effect only in high penetration departments (with a positive coefficient). This could be explained by the fact that in highly penetrated departments it is easier to be placed in the labor market, according to the innovation effect reviewed above.

  Finally, Katz (2012) conducted a study on job creation in the Dominican Republic, relying on panel data for the country’s 32 provinces. Contrary to the Chilean and Colombian models, the objective in this case was to study broadband contribution to the reduction of unemployment. The results in this case exhibit high impact. An increase in broadband penetration of 1% reduces unemployment in 0.29 percentage points. The other variables affecting unemployment in an indirect fashion are, as expected, the change in the number of industrial establishments, and the growing importance of the construction sector. 

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  TABLE 6.47

  Dominican Republic: Impact of growth in broadband penetration on unemployment reduction

  Source: Katz (2012)

  According to Table 6.44, an increase in broadband penetration of 1 per cent would diminish unemployment in 0.29 percentage points. For example, if the unemployment rate were to be 14 per cent, an increase of 1 per cent in broadband penetration would contribute to a reduction of unemployment to 13.71 per cent.

  The other variables that indirectly affect unemployment are, as expected, number of establishments between 2008 and 2009, and the intensity of the construction sector in a specific area in 2009. Therefore, a combination of increase in the number of establishment, investment in construction and broadband yields a positive effect in terms of job creation.

  It is considered that the contribution of broadband relative to the other two variables is too high. Part of this is due to the fact that the largest increase in broadband has taken place in Santo Domingo, the capital, and Altagracia, a tourism hub. Ideally, to refine the impact of broadband it would be necessary to include in the model specification a variable related to the intensity of the tourism sector. However, while data exists for three regions, Altagracia, Puerto Plata and Cibao Norte, data for the rest of the country is not captured. Therefore, it is impossible to introduce a variable measuring the intensity of tourism. As a result, the case confirms the contribution of broadband to job creation, although the range of impact might be overestimated.

  The results of the analyses also lead to validate the positive contribution of broadband to employment creation for less developed countries and regions. The following chart compiles the results of the existing literature (see table 6.48).

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  TABLE 6.48

  Comparative estimate of broadband impact on employment growth

  Source: Author

  In this case, all prior research and as well as the results of this study coincide that broadband has a positive impact on job creation. In particular, the Chilean and the Colombian cases, which are based on an extensive datasets, yield statistically significant positive coefficients. The other cases (Brazil and Dominican Republic) have also yielded statistically significant coefficients for the explanatory variable (broadband penetration) with sensible signs—positive when the independent variable is employment and negative when it is unemployment. While these studies are country-specific and cannot be applied directly to other nations, they provide an estimate of the potential employment gains that could result from effective broadband development. The positive relationship between broadband development and job growth is not in question. However, the magnitude of the impact should be the subject of further analysis, as the present studies are compiled using different methodologies and data samples.

  Coincident with these empirical studies, governments in the emerging world have begun to estimate the employment impact of broadband development programs. For example, the Malaysian Communications and Multimedia Commission (MCMC) estimated in 2008 that achieving 50 percent broadband penetration by 2010 could create 135,000 new jobs in the country. The MCMC further projected that the number of jobs created would reach 329,000 by 2022, based on 50 percent broadband penetration rate. 

6.7.2 Broadband, productivity and firm efficiency

Converging with the aggregate macro-economic research, the microeconomic analysis of the impact of broadband has helped understand the multiple effects that the technology has on firm performance. For example, several studies have been conducted to determine the relationship between broadband and productivity. Atrostic and Nguyen (2006) analyzed the productivity of 25,000 manufacturing plants according to data compiled by the US Census Bureau. They found a correlation in the range of 3.85 % and 6.07 % between intense use of business processes enabled by the introduction of broadband and labor productivity. A similar methodology was applied by Rincón-Aznar et al. (2006). The authors relied upon a database of enterprises using e-Business, which was compiled by the UK National Institute of Economics and Social Research. They found that the average impact of such processes (enabled by broadband access) resulted in 90% of firms in the service sector improving their productivity by 9.8%. The researchers also found that productivity improvement tends to be higher in certain segments of the service sector.

These results are consistent with the analysis of the e-Business watch survey, which determined that e-Business productivity gains depend on the industrial sector. The variable found to better explain the amount of broadband impact is the level of information-intensity of business functions. Based on this conclusion, Fornefeld et al. (2008) in a study commissioned by the European Commission estimate that broadband increases productivity of information-intensive firms by 20%. To summarize, microeconomic research has yielded the following estimates of firm productivity enhancement (see table 6.49).

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TABLE 6.49

Broadband-induced productivity improvement

Source: Forenfeld et al. (2008)

In addition to the impact on productivity, other microeconomic studies have focused on the impact of broadband technology on business expansion, product innovation and new business creation. With regards to business expansion, Clarke (2008) studied the impact of broadband access on exports of manufacturing and service firms. The analysis was performed for countries of medium and low levels of development in Eastern Europe and central Asia. The study controlled for variables such as firm size, industrial sector, foreign ownership, firm performance, level of domestic competition, international trade organization affiliation, progress in privatization, and telecommunications infrastructure. The author found that in the manufacturing sector firms with Internet access enabled by broadband generate 6% more foreign sales than the rest. In the service sector, broadband enabled firms generate between 7.5 % and 10 % more sales.

In addition to increasing exports, broadband has been found to have a positive impact on the development of new businesses. This results from the network effects of connectivity. When a large enough number of households are connected to broadband, the incentive to develop new businesses around information search, advertising and electronic commerce increases. For example, Crandall et al. (2007) estimate that the network effects of universal broadband access can have a multiplier of 1.17 on the investment in infrastructure. As a result of 40% lower broadband penetration in the United Kingdom, Liebenau et al. (2009) estimate the multiplier to be somewhat lower (0.33) for the British economy. 

6.7.3 Industrial sectors most impacted by broadband

As with output, the spill-over employment effects of broadband are not uniform across sectors. Two studies have identified differential levels of impact. According to Crandall et al. (2007), the job creation impact of broadband tends to be concentrated in service industries, (e.g., financial services, education, health care, etc.) although the authors also identified a positive effect in manufacturing (see table 6.50).

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TABLE 6.50

United States. Coefficient of broadband penetration in employment growth by sector (with significance at the 5% and 1% confidence level)

Source: Crandall et al. (2007)

 

N.A. Statistically not significant

In another study, Shideler et al. (2007) found that, for the state of Kentucky, county employment was positively related to broadband adoption in the following sectors (see table 6.51).

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TABLE 6.51

Kentucky: Differential impact of broadband by industry sector

Source: Shideler et al. (2007

The only sector where a negative relationship was found with the deployment of broadband (0.34 % - 39.68 %) was the accommodations and food services industry. This may result from a particularly strong capital/labor substitution process-taking place, whereby productivity gains from broadband adoption yields reduced employment. Crandall et al. (2007) also found a negative relationship for the Arts, Entertainment & Recreation sector, although it was not statistically significant.

Similarly, Thompson and Garbacz (2008) concluded that, for certain industries, "there may be a substitution effect between broadband and employmen.* It should therefore be considered that the productivity impact of broadband can cause capital- labor substitution and may result in a net reduction in employment. 

In summary, research is starting to pinpoint different employment effects by industry sector. Broadband may simultaneously cause labor creation triggered by innovation in services and a productivity effect in labor-intensive sectors. However, we still lack a robust explanation of the precise effects by sector and the specific drivers in each case. However, given that the sectoral composition varies by regional economies, the deployment of broadband should not have a uniform impact across a national territory.

6.7.4 Broadband and enterprise relocation

6.7.5 Broadband and entrepreneurship

6.7.6 Broadband as an impact on employment structure and distribution on a global scale

In addition to its impact on job creation, broadband also affects the global job distribution and the structure of employment. As broadband is facilitating the globalization of service provisions in highly value-added services such as accounting and IT related services as well as lower-skill services such as back-office functions and call center activities, jobs are migrating from high cost to low cost countries in these service sectors. In fact, the role of broadband in the international restructuring of job market in the service sector is increasing as more and more services can be traded as bandwidth increases. However, as Fornefeld et al. (2008) point out broadband-enabled outsourcing can benefit emerging regions benefitting from low cost labor and mature economies that leverage high-skilled workers.

For example, industrialized countries, such as the United States have been developing virtual call centers, which rely on home-based agents to complement/replace traditional call centers from emerging markets. This concept, enabled by home-based information technology and broadband infrastructure, has a number of distinctive advantages. It avoids overhead related to traditional contact centers, including real estate and utilities, as well as up-front investment/capital expenditures– particularly for rapid-growth companies. It lowers staff turnover due to work from home and flexible schedules, and improves service level and/or labor utilization due to flexible staffing – management of time of day and seasonal peaks. Finally, it provides greater responsiveness to unforeseen changes in demand and lowers labor factor cost by being able to attract talent at lower wages and benefits.

From an economic standpoint, a virtual call center located in an industrialized country offers 15%-30% cost advantage over the traditional centralized model (see figure 6.43).

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FIGURE 6.43

Traditional vs. Virtual Contact Center Cost Structure, Cost per Call

Source: Booz Allen analysis

(1) Flexible staffing model can allow for 15%+ reduction in agent FTE over model using 8 hour shifts

(2) Interviews indicate improvement in productivity from home-based agents Note: based on financial services case with 80% service level, 45 sec ASA, 272 AHT, 3 million rep calls per year

With this cost differential, in addition to the capability of staffing native English speakers, the virtual model represents a broadband approach to reverse the emerging market outsourcing trend (see figure 6.44).

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FIGURE 6.44

Number of Customer Service, Technical Support and Telemarketing Agents in the U.S. and India, 2000-2008

Source: U.S. Department of Labor, India's NASSCOM

In addition to the outsourcing trend, the growth of broadband has also affected the internal employment structure of both, mature and emerging economies through the increase of self-employment by creating environment for individuals to deliver their services directly to customers through broadband. For example, according to the Small and Medium Business Administration (SMBA) of South Korea, the nation's self-employed reached 235,000 in 2010, up 15.7 percent from the preceding year, and the number now accounts for about 1 percent of the economically active population. In the United States, 15.3 million workers (or 10.9% of the economically active population) are self-employed. Of these, 28.2% are in services such as information, financial activities, professional and business and education and health, all professions dependent to a large degree on broadband technology.

In addition to self-employment, broadband also assists with working from home. According to the Global Workplace Analytics, regular telecommuting in the United States grew by 73% between 2005 and 2011 (3.1 million) compared to only 4.3% growth of the overall workforce (not including the self-employed). In addition to the multiple benefits ranging from reduced carbon emissions to a reduction in real estate costs, tele-commuting opens up the labor market to those who might be disadvantaged, for instance by disability or by living in a rural location. Broadband also enables many more part-time opportunities, for instance trading on eBay as a form of supplementary income, but not a full-time job. In fact, according to the July 2005 e-Bay survey, more than 724,000 Americans reported that eBay was their primary or secondary source of income. In addition to these professional eBay sellers, another 1.5 million individuals said they supplement their income by selling on eBay. 

Another example of the impact of broadband on the job market is the emergence of the “virtual economy”, revenue generating opportunities, conducted in an informal, decentralized setting, in new emerging areas like micro-work, “gold farming” and gaming. The virtual economy is growing fast and contributes new job creations. As reported by Minn and Rossotto (2012), every year, about ten million people, half in the US, and the other half mainly in South Asia, earn an income from the micro-work platform Amazon Turk, launched over 15 years ago. Micro-work enables the division of a task into multiple “micro-tasks” and the micro-work platform enables a client to ask a crowd of “micro-workers” to respond to the task. The Non-Governmental Organization (NGO) Samasource has extended the concept of micro-work to highly distressed countries, including Southern Sudan. According to Samasource, each micro-worker in Sudan has been able to earn as much as $1,000 a year doing micro- work, with a quality similar to the Amazon Turk worker.

6.7.7 Potential negative impact of broadband on employment and management strategies