Keywords

1 Introduction

The interest for Information and Communication Technologies (ICT) has notably increased in recent years, leading to a flourishing of studies on their access, use and impact on economic, social, environmental and cultural dimensions. Furthermore, the diffusion of ICTs has been identified as a key driver of economic growth and sustainable development [1], and it is becoming a crucial tool in public administration, business, education, health and environmental areas. Against this backdrop, scholars have made visible progress on identifying various effects at aggregate level, such as on economic growth [2, 3], productivity [4–6], sector structures (e.g. finance and retail sales) and on the aggregate demand of technological items, among others.

More recently, the literature has moved towards analysing micro-effects, both at firm and individual level. Indeed, many effects from ICT usage occur within the household, affecting individual behaviour and decision-making processes. Gaining access to new technologies means to develop new technlological skills, to increase communication efficiency, to change preferences of media pattern used and to diversify the interaction with one’s own community, with important consequences across different dimensions. Psychological effects originated by the ability of ICT to influence individual behaviours can also be included. Possible examples are the effect of ICT-mediated communication on individual decisions as well as the use of web forums and global networks for advancing political goals, building social support nets, connecting disparate groups and providing opportunities for a broader influence of organizations, governments and individuals [7].Footnote 1 For instance, it has been found that Internet use was associated with a higher probability of voting in the 2000 US election [9].Footnote 2 Moreover, a large body of research has highlighted that Internet has become a primary source of information. For example, about 50% of the US citizens have indicated the Internet as their main source of political news [11].

In this perspective, improving access to information is probably the most important effect of ICT diffusion, as a result of the broad range of impacts this could have on everyday life. In particular, Internet users have been found to have great advantages in activities such as price comparison and job seeking. In addition, some studies have shown that consumers can save important amounts by buying goods and services online. For example, it was reported that buying electronics on web platforms generates an average saving of 16% compared to purchasing at listed prices [12]. Similar results are reported in the case of books and CDs [13] and in the case of new cars [14]. At the same time, Internet use is supposed to smooth search and matching processes in several areas, including the job market. Recent economic literature points out that online job search is effective in various aspects. For example, it has been shown that Internet use reduces by approximately 25% unemployment duration [15] and that Internet increases the probability of labour force participation for married women [16]. Other studies show that access to broadband services is associated with higher employment rates, especially in rural and isolated areas [17]. Also, some evidence suggests that employed individuals who use the Internet to search for jobs are more likely to change jobs and to gain a better wage in the transition [18].

Despite the consensus about the importance of a more complete understanding of these dynamics, empirical studies on the effects of ICT diffusion on individual dynamics are still limited. Therefore, many questions remain still unanswered, especially in the context of developing countries. In fact, due to the availability and quality of data, most of the academic research on ICTs has been conducted in developed economies. But it is probably within the context of developing countries where innovative lines of analysis can be found and explored, proposing a renewed perspective on the relation between ICTs and development. ICT can be an important channel for diffusing information about social and economic programs and for promoting the full participation of the community in their implementation. For instance, the Internet can constitute a powerful tool to provide information about scholarship programs and to obtain a more balanced distribution of educational opportunities.

This paper contributes to the ICT literature by analysing the role of Internet use in allocating scholarships among students in Chile. The hypothesis is that the use of the Internet affects positively the probability of being awarded by a scholarship through access to complete and updated relevant information. The empirical exercise uses statistical information from the Chilean National Household Surveys between 2000 and 2009, when Internet access was still limited but increasing rapidly. Thus, the study focuses on the potential information effects in a period where technology was still unevenly distributed across different socio-economic population groups. The article is organized as follows. Section 12.2 shows the main patterns of ICT diffusion in Chile. Section 12.3 displays the empirical analysis and it discusses the main results. Finally, Sect. 12.4 concludes and establishes some further research areas.

2 Main Patterns of ICT Diffusion in Chile

In the last decade, the Internet access increased considerably among the Chilean population. In 2000, less than 10% of Chilean households had Internet access, and this figure surged to 30% in 2009 and to more than 65% in 2014 (Fig. 12.1). However, this aggregate picture hides major differences among locations and population groups. As expected, the Internet access is much higher in urban than in rural areas. In 2009, only 7.2% of the rural households had an available Internet connection, compared with 32% of those households located in urban areas. Not surprisingly, the unequal distribution of ICT access among the population is confirmed by analysing the Internet penetration rates by income and education quintiles. In 2009, only 7% and 15% of households in the first and second income quintiles benefit from Internet access, respectively (Fig. 12.2). By contrast, in the fourth and fifth quintiles, more than 42% and 70% of households had Internet access, respectively. Moreover, the differences in the Internet access are not homogeneous along subsequent population segments, and the fifth quintile concentrates the bulk of the Internet penetration. Likewise, the distribution of Internet access by educational quintiles – measured by the average education years of adults in the household – follows a similar pattern across households. In 2009, the Internet access rates in the first and second quintile were 0.7% and 3%, respectively. For the households in the fourth and fifth educational quintiles, penetration rates for Internet reached 18% and 53%, respectively. Thus, to a large extent the access to Internet reflects pre-existing socio-economic inequalities across households.

Fig. 12.1
figure 1

Internet access at household level, 2000–2014 (Source: author’s elaboration based on National Household Surveys)

Full size image
Fig. 12.2
figure 2

Internet access by income quintiles at household level, 2009 (Source: author’s elaboration based on National Household Survey)

Full size image

The type of Internet connection also reflects pre-existing socio-economic inequalities across households. In 2009, the broadband access connection was available only in 5% and 11% of households with an available Internet connection in the first and second income quintiles, respectively. By contrast, these figures reached 35% and 62% in fourth and fifth income quintiles. In addition, differences of Internet use are observed not only across households but also within households. Among households with an available Internet connection, only 40% of the components actually use it, which shows that Internet access does not translate into use [19, 20]. The different population cohorts also play a relevant role. As expected, the Internet use decreases monotonically with age of the population. Indeed, in 2009 more than the 70% of the population aged between 15 and 24 years used the Internet, while only 22% of the population aged between 50 and 59 used the web.

3 Empirical Approach and Econometric Results

3.1 Empirical Approach

The empirical approach to analyse the determinants of the probability of having a scholarship is based on the following Probit equation:

$$ \begin{array}{c} \Pr \left({\mathrm{Scholarship}}_i=1\right)=\varPhi (\alpha +{\beta_0}^{\ast }{\mathrm{Income}}_j+{\beta_1}^{\ast }{\mathrm{Education}}_j\\ {}+{\beta_2}^{\ast }{\mathrm{Family}\;\mathrm{Size}}_j+{\beta_3}^{\ast }{\mathrm{Rural}}_{j\ }\\ {}+{\beta_4}^{\ast}\mathrm{Head}+{\beta_5}^{\ast }{\mathrm{Female}}_j\\ {}+{\beta_6}^{\ast }{\mathrm{Internet}}_j)\end{array} $$
(12.1)

where Pr (Scholarship i = 1) is the probability that the individual i is granted by a scholarship.Footnote 3 The Probit model assumes that the error term is normally distributed with mean 0 and variance σ equal to 1, and Φ(.) corresponds to the cumulative distribution function for a standard normal random variable. In this empirical model, the probability that an individual is granted with a scholarship depends on several variables. The variable Income corresponds to the per capita equivalent income of the household,Footnote 4 and Education corresponds to the household education level measured by the average level of educational years of adults (age ≥18). Given that the scholarship system focuses on more vulnerable students, we expect income to be negatively correlated with the probability of having a scholarship. By contrast, the education level of the household can play an important positive role because of the effects on a better access and use of information related to social programs. In addition, it can capture some other unobservable characteristics that can affect positively the probability of obtaining a scholarship, such as parent motivation towards educational achievements.

The variable Family Size is the number of individuals in the household and Rural is a dummy variable that controls for the area where the household is located. Meanwhile, Head is a dummy variable that takes the value of 1 for households in which the head is a woman. There are several studies that discuss the peculiarities of households having a female head. On one hand, it is generally argued that such households evidence some disadvantages, for example, higher levels of poverty. This is associated to the fact that the head of the household may work less time and that these households generally have lower adult members that generate income. On the other, women are often more attentive about the nutrition and the education of the children, and it is intuitive to expect that students of these households would be more likely to be granted by educational scholarships. Female is a dummy variable that takes the value of 1 if the individual is a woman, being the only variable at individual level. The Appendix 12.1 shows basic statistics of explanatory variables, and the Appendix 12.2 displays the correlation matrix.

The main hypothesis to test in this empirical section is that the use of the Internet at household level is positively correlated to the scholarship awarding of primary students living in that household. The Internet might provide advantages in terms of scholarship information, application procedures, updates and in promoting social participation. We specify two different measures on Internet, which is our core variable. The variable Internet 1 is a dummy variable that takes the value 1 if at least one adult in the household uses the Internet. The variable Internet 2 corresponds to the proportion of individuals within the household that use Internet (see Table 12.1). Thus, with these two variables, we attempt to control for both the Internet use and the Internet use intensity among adults within the household. Finally, we also add municipality fixed effects, to account for different scholarship provision levels.

Table 12.1 Internet use and scholarship attainment: definition of estimation variables
Full size table

Therefore, the empirical approach is based on an equation in which the probability for a student of obtaining a scholarship is associated to several household characteristics, like income and education, while the only variable defined at student level is Female. In a general setting, this is likely to create a problem of relevant omitted variable. In particular, the model does not control by individual capabilities that surely affect the probability of obtaining a scholarship, such as academic proficiency. Therefore, the estimation results would be inconsistent and biased. Nevertheless, our focus on primary school greatly reduces this problem. Indeed, the main determinants of the primary scholarship attainment are the household socio-economic characteristics. The statistical information comes from the National Household Surveys 2006 and 2009, implemented by Ministerio de Desarrollo Social. This survey covers a wide range of social and economic characteristics at individual and household level. Each year the survey covers around 70,000 households (250,000 individuals) and the surveys are statistically representative at national level.

3.2 Econometric Results

The econometric results are provided in Table 12.2. We first implement baseline estimations (model 1) and then we sequentially add the core variables (Internet 1 and Internet 2) (model 2 and 4) and Municipalities fixed effects (model 3 and 5). A robust result of the estimations is that the effect of income on the probability of obtaining a scholarship is negative and significant. Thus, students in household with lower income are more likely to be granted by a scholarship. This is consistent with social and redistribution objectives of the young student scholarship programs in Chile, as more disadvantageous students from a socio-economic dimension should be more likely to obtain a scholarship. The level of education in the household also seems to play a relevant role. In fact, students living in more educated households are more likely to obtain a scholarship, on average and ceteris paribus. This is consistent with the idea that more educated households are associated to a better and more efficient use of information. Also, a more educated household can have a higher commitment towards educational achievements.

Table 12.2 Internet and primary scholarship attainment: Probit model estimations
Full size table

Additionally, there is evidence that students living in households where the head is a woman are more likely to be granted by a scholarship, though its magnitude is small. According to model (5), primary students in a household where the head is a woman are 0.8% more likely to be granted by a scholarship. Meanwhile, the rural location condition displays mixed evidence. This result is not surprising given the scholarship schemes available, with different objective and population targets. Furthermore, the correlation of the location condition with other control variables suggests being cautious about its interpretation.

Our main interest concerns the Internet variables. In the models (2) and (3), the coefficient is positive and significant at 1%. This shows that the students living in a household where at least one adult uses the Internet have higher probability of being granted by a primary scholarship. In terms of magnitude, a student in household with Internet access increases the probability of having a scholarship by 2%. In addition, the estimated coefficients in the models (4) and (5) are also positive and significant at 1%. Thus, the intensity of Internet use among adults within the household is also positively correlated to the probability for a primary student within the household of being granted by a scholarship. Thus, not only the Internet use but also its use intensity within the household is correlated with the individual probability of having a primary scholarship. A key channel that could explain this correlation is having access to improved and updated information through the Internet, particularly about when and how to participate in student scholarship programs.

We acknowledge that it is not possible to interpret this evidence in terms of a causal relationship, so we interpret our results as a correlation. Also, the fact that the scholarship variable is measured at individual level, while the Internet use is measured at household level, might also generate doubts on the relevance of the empirical results. Nevertheless, it should be considered that the main determinants of primary scholarship attainment are actually related to household characteristics. Thus, we think the empirical evidence of such a strong correlation between Internet use and scholarship attainment should not be underestimated. This correlation, controlling by the main socio-economic determinants of scholarship attainment, suggests that the Internet play a role on providing better access to relevant information and promoting greater social participation in public programs.

Nevertheless, the descriptive evidence presented in the section II and evidence from previous studies clearly show that ICT access and usage are largely determined by socio-economic characteristics such as income and education [19, 22]. Thus, more advantageous population groups are more likely to benefit from ICT diffusion. In our case, primary students living in households with Internet access and usage are more likely to be granted by a scholarship, but households with higher education and income are precisely the ones that tend to have more ICT access. Thus, we can expect that the positive effect of ICT diffusion will be concentrated in these households. This illustrates the dual role of ICT. On one hand, ICT promotes social participation and greater access to information with potential large positive effects. However, already advantaged population groups are more likely to benefit more from it.

In sum, this result confirms the role of the Internet in allowing a better access to information and greater social participation. But given that ICT diffusion is not homogeneous across population groups, the benefits will tend to be concentrated in more advantaged population groups. From a public policy perspective, this evidence shows that Internet access and usage can be an important channel for both diffusing information about social and economic programs and promoting the full participation of the community in their implementation. But at the same time it suggests that it is critically important to address the digital divide in order to fully expand its benefits. Therefore, there is a need for proactive and well-designed public policies that could not only promote ICT access but also spread out its benefits across the population.

4 Conclusions

The effects of ICT at household and individual level are multiple. Most of the studies at micro level have tried to disentangle this multiplicity of effects by focusing on specific issues. However, the existing literature is far from being complete and exhaustive. There is a lack of empirical analysis on some specific effects, and the dynamic nature of ICT impacts has also been overlooked. In this paper, we contribute to the empirical literature by providing evidence on how ICT diffusion improves access to information and promote social participation in a particular case: scholarships programs for primary students. The evidence presented suggests that primary students in households that use the Internet have larger probability of being awarded by a scholarship, even after controlling by socio-economic characteristics. However, given that ICT diffusion is not homogeneous across population groups, the main benefits from this are expected to be concentrated in more advantageous groups as well. This illustrates both the potential and risks that the ICT diffusion process entails across different dimensions.

Moving forward, it is not certain that observed ICT impacts could persist with the same magnitude and direction found in the existing literature, and there are reasons to suppose that ICT impacts could change along two dimensions: dynamically and cross-sectional. The first simply means that ICT impact could change over time as ICT expands. This hypothesis is supported by the fact that ICT evolves continuously, reaching every year higher levels of sophistication and potentials. If the technological frontier is moving, it is reasonable that its effects will move too. Moreover, variations of ICT impacts over time could simply be given by the taking over of a new generation of ICT users. So far, researches have analysed ICT impact using samples of individuals that approached ICT at a certain stage of their life, but in the future it will be possible to analyse the impacts on the generation born after the beginning of the ICT revolution, whose members have always dealt with ICT since early stages of life. Cross-sectional differences are another possible further extension of the ICT impact literature, given its close connection with the digital divide and digital inequality. For instance, it would be interesting to study possible differences in ICT impacts across different individual characteristics, such as races, educational levels and gender.

The relevance of new technologies in the development path justifies an increasing effort by international institutions, academia and scholars to achieve a better understanding of the ICT diffusion process. Early visions were generally optimistic in considering it as an equalizing factor both at international and at domestic level, but successive scholars have highlighted the risk that ICT might worsen pre-existing inequalities. This is a key area of further research. Considering that ICT have no reason to exist on itself but only on the benefits they have for individuals, it is clear that the research agenda has unavoidable challenges ahead.