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The remainder of this paper is structured as follows. Section 2 sketches potential labor market effects of information and communication technology (ICT) and broadband internet and reviews previous empirical evidence. Section 3 describes the broadband data and discusses the identification strategy. Section 4 presents the estimated model of employment growth, the employment data, and descriptive statistics. Section 5 presents the estimation results. Section 6 concludes.
Against this background of previous research, this study seeks to contribute evidence on the employment growth effects of broadband availability at the establishment level, using German data, and thereby to fill an empirical research gap.
To identify the causal relationship between DSL availability and employment growth, this study seeks to exploit sources of exogenous variation in the former variable. There exist two such sources, one each for rural Western Germany and urban Eastern Germany, which potentially allow for the construction of instrumental variables.
Besides the above-discussed problem of endogeneity (the main motivation for the proposed IV approach), another rationale for employing IV regression is to address measurement error in the explanatory variable (see Angrist and Pischke 2009, p. 127 sqq. and Hausman 2001), which biases OLS estimates towards zero. Here, the main source of measurement error is that DSL availability is observed only at the municipality level, while employment growth is observed at the establishment level. By using variation in DSL availability driven by the instruments, attenuation bias can be alleviated. However, there is also measurement error in the instruments themselves, namely if a municipality is classified as being above the distance threshold, while the establishment location is in fact below the threshold, or vice versa. Yet, this problem can be addressed by using alternative instruments (see robustness checks).
Another caveat regarding the interpretation of the estimates is that only the availability, but not the adoption of broadband is observed. As discussed by Czernich (2014), the effects of broadband availability are necessarily closer to zero than the effects of its adoption if, as seems likely, broadband affects firms through its actual use by firms. At the same time, however, note that the observation period captures a relatively late stage of DSL rollout (the late-coming municipalities), when the DSL technology was already well established and easily affordable even to households. Most establishments therefore likely adopted DSL as soon as it became available, so the difference between availability and adoption should be small, and the estimated effects of DSL availability should largely reflect the effects of DSL adoption.
The table indicates for Western Germany that municipalities above the distance threshold had slightly lower employment levels in 1999 than municipalities below the threshold. However, there are no significant differences in past employment growth and local labor market characteristics such as the share of high-qualified workers and the wage level. This slight imbalance is accounted for in the estimations by controlling for the contemporary values of the same covariates. For Eastern Germany, in contrast, splitting municipalities by the value of the OPAL dummy generates two subsets that differ significantly in their base-year levels and growth rates of employment. Therefore, it cannot be credibly held that the OPAL dummy would be a valid IV in the model to be estimated, and hence it is not used in this study.
OLS results for Eastern German establishments are presented in Table 5. There is no indication of a significant effect of DSL on employment growth, potentially due to measurement error in the DSL variable. Moreover, model fit is relatively poor for the Eastern sample. A possible reason for this pattern is the more urban geographic structure of the Eastern sample, meaning that this sample contains a greater diversity of establishments and hence, a larger variation of employment growth, some of which may be explained by unobserved factors.
The findings obtained so far raise the question why broadband apparently spurs job creation in services but appears to have the opposite effect for manufacturing. One answer might be that service firms are more intense users of broadband (Arntz et al. 2016), and that their internet use is complementary to employment. Akerman et al. (2015) investigate this channel of effects, failing to falsify it against a number of likely alternatives (such as demand-side product-market effects). Following this logic, the positive employment growth effect of DSL in the service sector might be driven by firms for which information is a key input and ICTs, such as broadband, are key technologies.
These results are displayed in Table 6 (OLS) and Table 7 (IV, Western Germany only). The estimates suggest positive employment growth effects for knowledge-intensive industries in both regional subsamples, as well as for computer-intensive industries in (rural) Western Germany. Although this is a plausible pattern of results, it does not necessarily imply that knowledge- or computer-intensive industries are driving the positive effect found for Western German services, as the respective coefficients are not significantly different. For Eastern Germany, reassuringly, a significantly positive coefficient is found at least for the relatively small group of knowledge-intensive industries.
In another robustness check, similar to Falck et al. (2014), as an alternative to instrumenting DSL availability, a long-difference model is estimated (technically a first-difference model) which identifies the effect of DSL based on the change in DSL availability between the pre-DSL period (up to 1999) and the main observation period, when DSL was available. This model can be formulated as
Regarding Western Germany (Table 9), at least for \(t = \left( {2006, 2007} \right)\), these estimations confirm the positive employment growth effect of DSL availability in the service sector, whereas the negative employment growth effect for manufacturing establishments found in the main specification once more is not confirmed. For \(t = 2008\), no significant employment growth effects are found using the long-difference model. This could be due to the 2008/2009 recession (due to first-differencing, year fixed effects cannot be used in this specification). For Eastern Germany (Table 10), partly positive employment growth effects are found for both sectors. However, the pattern of estimates for Eastern Germany seems less plausible and robust across different values of \(t\). Regarding quantitative interpretation, the estimates for \(t = 2007\) and service establishments imply that a ten percentage point increase of DSL availability (from zero) between 1999 and 2007 is related to an increase of employment growth by 1.95 percentage points (West), respectively 0.86 percentage points (East).
In line with previous empirical literature, the empirical results for Western Germany suggest that broadband expansion has helped service establishments create jobs. The magnitude of this employment growth effect is substantial: A ten percentage point increase in DSL availability is associated with an increase in the employment growth rate of two to three percentage points. Also in line with previous research, a significantly positive effect is found for knowledge-intensive industries. In contrast, for Western German manufacturers a negative employment growth effect of similar magnitude is found, which however turns out to be less robust to changes of the estimated specification. The internal validity of the findings is supported by robustness checks concerning in particular the definition of the instrument.
The finding of a service-biased job creation effect, or even a reallocation of job creation from manufacturing to services, is in line with theoretical considerations and previous empirical literature, which finds the same sectoral pattern. Due to the focus on employment growth at the establishment level and broadband availability at the establishment location, the findings of this study suggest that broadband affects employment growth through its productive use in firms, with service firms being more apt to use it than manufacturers. Moreover, broadband may induce outsourcing of manufacturing jobs to the service sector, which would be in line with the opposite signs estimated for both sectors, but cannot be identified with the data at hand. Furthermore, a fast broadband connection may enable employees to work from home and enable more flexible work hours. Thereby, broadband can help reconcile work and family duties and thus increase labor supply, notably for high-qualified women with children (Dettling 2017). These channels of effects, which would merit further empirical investigation given the necessary data, are also in line with the service-biased employment growth effect of broadband internet found in this study. ff782bc1db