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on Information and Communication Technologies |
| By: | Valentino Larcinese; Luke Miner |
| Abstract: | What are the political consequences of the diffusion of broadband internet? We address this question by studying the 2008 US presidential election, the first political campaign where the internet played a key role. Drawing on data from the FEC and the FCC, we provide robust evidence that internet penetration in US counties is associated with an increase in turnout, an increase in campaign contributions to the Democrats and an increase in the share of Democratic vote. We then propose an IV strategy to deal with potential endogeneity concerns: we exploit geographic discontinuities along state borders with different right-of-way laws, which constitute the main determinant of the cost of building new infrastructure. IV estimates confirm a positive impact of broadband diffusion on turnout, while the pro-Democratic Party effect of the internet appears to be less robust. |
| Keywords: | internet diffusion, political economy of the media, United States elections, turnout, campaign contributions |
| JEL: | D72 L86 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_6882&r=ict |
| By: | Robert W. Fairlie; Peter Riley Bahr |
| Abstract: | This paper provides the first evidence on the earnings, employment and college enrollment effects of computers and acquired skills from a randomized controlled trial providing computers to entering college students. We matched confidential administrative data from California Employment Development Department (EDD)/Unemployment Insurance (UI) system earnings records, the California Community College system, and the National Student Clearinghouse to all study participants for seven years after the random provision of computers. The experiment does not provide evidence that computer skills have short- or medium-run effects on earnings. These null effects are found along both the extensive and intensive margins of earnings (although the estimates are not precise). We also do not find evidence of positive or negative effects on college enrollment. A non-experimental analysis of CPS data reveals large, positive and statistically significant relationships between home computers, and earnings, employment and college enrollment, raising concerns about selection bias in non-experimental studies. |
| Keywords: | computer skills, earnings, employment, college enrollment, experiment |
| JEL: | I20 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_6860&r=ict |
| By: | Annunziata, Marco; Bourgeois, Hendrik |
| Abstract: | A new wave of innovation is beginning to disrupt industry on a global scale. It constitutes a tremendous opportunity for faster productivity growth, but also a potential disruption to a number of economic sectors and to job markets. Academic research and the public debate have focused mostly on the threat that innovation poses to jobs and wages. This paper instead suggests that (i) these same technological disruptions make human capital more important than ever for companies' strategies; (ii) greater attention needs to be devoted to new forms of complementarity between new technologies and human capital. While some jobs will be displaced, the greatest impact of innovation will come in the way that many jobs will be transformed; the evidence to date supports the authors' view that innovation will once again result in more and better jobs - but much work needs to be done to optimize the transition. In particular, more effort should be devoted to (i) understanding what new skills will be needed, and how existing jobs will change; (ii) upgrading education and professional training schemes; (iii) reforming labor market institutions to support a future where a larger share of workers will change jobs and employers more frequently, and more people will work independently in a crowdsourcing or "gig economy" framework; (iv) reforming social benefits systems and bolstering social safety nets to smooth the economic transition and cushion the impact on the worst-affected workers. As innovation disrupts a growing number of industries, human capital strategies will need the collaboration of companies, educational institutions, governments and multilateral policy agencies. This paper presents an analysis of the challenges, addresses the key areas of action, and puts forward some specific proposals, including policy actions, industry initiatives, and further research projects. The authors argue that the G20 could and should champion a comprehensive approach to leverage digital-industrial innovations for faster job creation and growth, with measures to re-align demand and supply of skills, labor market reforms, redesigned social safety nets, measures to promote digital innovation and facilitate the adoption of skills-augmenting technologies. Private sector companies should strengthen training programs. International cooperation, standards harmonization and interoperability will be essential to maximize the benefits and minimize the disruptions - the G20 can therefore play a key role. |
| Keywords: | innovation,productivity,technological unemployment,training,education,manufacturing,R&D,investment |
| JEL: | J20 J23 J24 J62 J68 O32 O33 M5 I28 E24 D24 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:ifwedp:201828&r=ict |
| By: | Patrick Waelbroeck |
| Abstract: | The blockchain is a technology that goes beyond timestamping, bitcoin and secure financial transactions. The development of an ecosystem around smart connected objects will probably not happen without the blockchain (in one form or another). The blockchain opens the door to the liquification of the physical world, to the economy of real-time micro-transactions and to smart data sharing. However, it is necessary to distinguish between the different types of blockchains, especially between public and private blockchains, because their economic properties are contrasted. Moreover, governance issues in public blockchains seem to indicate that the technology alone cannot guarantee trust. |
| Keywords: | blockchain, bitcoin, ether, security, payment, governance, trust, oracles, forks, hash, smart contracts, tokens, smart locks, technology diffusion, crypto-currency, financial privacy |
| JEL: | E51 G34 H41 L14 L52 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_6893&r=ict |
| By: | Ioana Marinescu; Nadav Klein; Andrew Chamberlain; Morgan Smart |
| Abstract: | Online reviews are a powerful means of propagating the reputations of products, services, and even employers. However, existing research suggests that online reviews often suffer from selection bias—people with extreme opinions are more motivated to share them than people with moderate opinions, resulting in biased distributions of reviews. Providing incentives for reviewing has the potential to reduce this selection bias, because incentives can mitigate the motivational deficit of people who hold moderate opinions. Using data from one of the leading employer review companies, Glassdoor, we show that voluntary reviews have a different distribution from incentivized reviews. The likely bias in the distribution of voluntary reviews can affect workers’ choice of employers, because it changes the ranking of industries by average employee satisfaction. Because observational data from Glassdoor are not able to provide a measure of the true distribution of employer reviews, we complement our investigation with a randomized controlled experiment on MTurk. We find that when participants’ decision to review their employer is voluntary, the resulting distribution of reviews differs from the distribution of forced reviews. Moreover, providing relatively high monetary rewards or a pro-social cue as incentives for reviewing reduces this bias. We conclude that while voluntary employer reviews often suffer from selection bias, incentives can significantly reduce bias and help workers make more informed employer choices. |
| JEL: | J2 J28 L14 L86 |
| Date: | 2018–03 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:24372&r=ict |
| By: | Steusloff, Tatjana (Department of Economics of the Duesseldorf University of Applied Sciences); Krusenbaum, Lena |
| Abstract: | Der steigende Umsatz im Online-Handel lässt eine zunehmende Bereitschaft von Konsumenten erkennen, Produkte online zu erwerben. Wird eine Kaufentscheidung online getroffen, dann liegt eine Informationsasymmetrie zugunsten des Verkäufers vor. Daher sind für die Konsumenten Informationen zu den gewünschten Kaufobjekten von hoher Bedeutung, um die Produktqualität beurteilen zu können. Neben den Produktinformationen des Händlers beeinflussen die Kaufentscheidung der Konsumenten zunehmend von Käufern verfasste Online-Rezensionen (OR). Diese werden von potentiellen Käufern oft als sehr glaubwürdig wahrgenommen, da sie von einem tatsächlichen Konsumenten verfasst wurden. In dieser Studie wurde die Wirkung dieser Rezensionen auf die Zahlungsbereitschaft von Käufern bei Amazon untersucht. Die Ergebnisse legen den Schluss nahe, dass vom Konsumenten als positiv wahrgenommene Online-Rezensionen einen signifikant positiven Einfluss auf die Zahlungsbereitschaft haben, negativ wahrgenommene ORs diese jedoch tendenziell senken. Beeinflusst die OR die Qualitätswahrnehmung positiv, so erhöht sich tendenziell die maximale Preisbereitschaft von potenziellen Käufern. Die Erkenntnisse dieser Studie sind für alle Unternehmen relevant, die ihre Produkte bei Amazon verkaufen. Sie können mit diesem Wissen u.a. ihr Rezensionssystem optimieren und ihre Preispolitik so ausrichten, dass Umsätze optimiert werden können. |
| Abstract: | Increasing online sales indicate a rising willingness of consumers to buy their products online. For a purchase decision made online there often exists an information asymmetry in favor of the seller. Therefore, in-formation about the desired purchase object are of high importance for the potential consumers in order to assess product quality. In particular, consumer-written online reviews (OR) increasingly influence the online purchase decision, since they are written by actual consumers and thus perceived as very credible. In this study, the effect of these reviews on Amazon consumers’ willingness to pay (WTP) was analyzed. Results indicate an increased willingness to pay if consumers perceive ORs positively, whereas negative reviews tend to lower the WTP. If OR influences the quality perception positively, the maximum willingness to pay of potential buyers tends to increase. The findings of this study are relevant to all companies that sell their products on Amazon. With this knowledge, they can tailor their pricing policy to optimize sales. |
| Keywords: | Online-Rezensionen, Amazon, Preisbereitschaft, Kaufentscheidung, Online Ratings, Willingness-to-pay, Purchase Decision |
| JEL: | L1 G1 |
| URL: | http://d.repec.org/n?u=RePEc:ddf:wpaper:39&r=ict |
| By: | Lin William Cong; Zhiguo He |
| Abstract: | Blockchain technology features decentralized consensus as well as tamper-proof and algorithmic executions, and consequently enlarges the contracting space through smart contracts. Meanwhile, the process of generating decentralized consensus, which involves information distribution, necessarily alters the informational environment. We analyze how decentralization improves consensus effectiveness, and how the quintessential features of blockchain reshape industrial organization and the landscape of competition. Smart contracts can mitigate information asymmetry and deliver higher social welfare and consumer surplus through enhanced entry and competition, yet blockchains may also encourage collusion due to the irreducible distribution of information, especially in consensus generation. In general, blockchains can sustain market equilibria with a larger range of economic outcomes. We further discuss anti-trust policy implications targeted to blockchain applications, such as separating consensus record-keepers from users. |
| JEL: | D4 D8 G2 L13 L4 O3 |
| Date: | 2018–03 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:24399&r=ict |
| By: | Wuttigrai Ngamsirijit (National Institute of Development Administration) |
| Abstract: | It is critical for a public sector to raise awareness and fight against the corruption. Among many government projects, enhancing transparency through improving public service operations and processes can be seen as one of the solutions. This study presents the lesson learnt from the transparency project performed by government agencies including selection process and criteria, selected processes, attitudes towards the project, and various obstacles and limitations in deriving the right process. These findings are synthesized and an analytics framework of public service process selection for transparency is then proposed. Such framework incorporates data analytics methodologies and techniques so that it can be further developed to build transparency in today?s digital age. |
| Keywords: | Service operations, Analytics, Transparency, Anti-corruption |
| JEL: | L32 O21 M29 |
| Date: | 2017–10 |
| URL: | http://d.repec.org/n?u=RePEc:sek:iacpro:5907847&r=ict |
| By: | Rui Fan (School of Management, Swansea University); Oleksandr Talavera (School of Management, Swansea University); Vu Tran (School of Management, Swansea University) |
| Abstract: | This study examines whether stock indicators are affected by information in social media such as Twitter. Using a daily sample of tweets with a FTSE 100 firm name over two years, we find insignificant associations between tweets/bot-tweets and stock returns whereas there is a strongly significant association with volatility and trading volume. Using a high-frequency sample, we detect a positive (negative) impact of tweets (bot-tweets) on stock returns. The impact of bot-tweets vanishes within 30 minutes. The results for volatility and trading volume are consistent with the daily data analysis. In addition, event study reveals a bounce-back pattern of price reactions in response to negative retweets. Abnormal increases in tweets/bottweets have significant effects on stock volatility, trading volume and liquidity. |
| Keywords: | Social media bots, investor sentiments, noise traders, text classification, computational linguistics |
| JEL: | G12 G14 L86 |
| Date: | 2018–03–23 |
| URL: | http://d.repec.org/n?u=RePEc:swn:wpaper:2018-30&r=ict |
| By: | Julien Prat; Benjamin Walter |
| Abstract: | We propose a model which uses the Bitcoin/US dollar exchange rate to predict the computing power of the Bitcoin network. We show that free entry places an upper-bound on mining revenues and we devise a structural framework to measure its value. Calibrating the model’s parameters allows us to accurately forecast the evolution of the network computing power over time. We establish the accuracy of the model through out-of-sample tests and investigation of the entry rule. |
| Keywords: | Bitcoin, blockchain, miners, industry dynamics |
| JEL: | D41 L10 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_6865&r=ict |