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on Information and Communication Technologies |
| By: | Tianshu Sun (Marshall School of Business, University of Southern California, Los Angeles, CA 90089 United States); Zhe Yuan (School of Economics, Zhejiang University, Hangzhou 310000 China); Chunxiao Li (Alibaba Group); Kaifu Zhang (Alibaba Group); Jun Xu (Alibaba Group) |
| Abstract: | Personal data has become a key input in Internet Commerce, facilitating the matching between millions of customers and merchants. Recent data regulations in China, Europe and US restricts Internet platforms' ability to collect and use personal data for personalized recommendation and may fundamentally impact Internet Commerce. In collaboration with the world's largest E-commerce platform, we conduct a large-scale field experiment to measure the potential impact of data regulation policy, and to understand the value of personal data in Internet Commerce. For a random subset of 555,800 customers on Alibaba platform, we simulate the regulation by banning the use of personal data in the homepage recommendation algorithm and record the matching process and outcomes between these customers and merchants. Compared to the control group with personal data, we observe a significant higher concentration in the algorithmic recommendation of products in the treatment group and a very sharp decrease in the matching outcomes as measured by both customer engagement (clickthrough rate and product browsing) and market transaction (GMV). The negative effect is disproportionate and more pronounced for niche merchants and customers who would benefit most from E-commerce. We discuss the economic impact of data regulation on Internet Commerce, as well as the role of personal data in generating value and fostering innovations. |
| Keywords: | Personal Data, Privacy Regulation, E-commerce, Field experiments, Personalization, Market Structure |
| Date: | 2021–10 |
| URL: | http://d.repec.org/n?u=RePEc:net:wpaper:2110&r= |
| By: | Julia Cage (Département d'économie); Edgard Dewitte (Département d'économie) |
| Abstract: | We study electoral campaigns over the long run, through the lens of their spending. In particular, we ask whether changing media technologies and electoral environments impacted patterns of spending and their correlation with electoral results. To do so, we build a novel exhaustive dataset on general elections in the United Kingdom from 1857 to 2017, which includes information on campaign spending (itemized by expense categories), electoral outcomes and socio-demographic characteristics for 69, 042 election-constituency candidates. We start by providing new insights on the history of British political campaigns, in particular the growing importance of advertising material, including via digital means, to the detriment of paid staff and electoral meetings. We then show that there is a strong positive correlation between expenditures and votes, and that overall the magnitude of this relationship has strongly increased since the 1880s, with a peak in the last quarter of the 20th century. We link these transformations to changes in the conduct of campaigns, and to the introduction of new information technologies. We show in particular that the expansion of local radio and broadband Internet increased the sensitivity of the electoral results to differences in campaign spending. These results encourage greater contextualization in the drafting of campaign finance regulations. |
| Keywords: | Elections; Campaign finance; Electoral expenditures; Information technologies |
| JEL: | D72 P48 H7 |
| Date: | 2021–09 |
| URL: | http://d.repec.org/n?u=RePEc:spo:wpmain:info:hdl:2441/1dp7827s4n8ht8fk3qhmeuvd0o&r= |
| By: | D. LASHKARI (Boston College); A. BAUER (Insee - Crest); J. BOUSSARD (Commission européenne - Crest) |
| Abstract: | Relying on a novel dataset on hardware and software investments in the universe of French firms, we document a robust within-industry correlation between firm size and the intensity of IT demand. To explain this fact, we argue that the relative marginal product of IT inputs may rise with firm scale, since IT helps firms deal with organizational limits to scale. We propose a general equilibrium model of industry dynamics that features nonhomothetic production functions compatible with this mechanism. Estimating this production function, we identify the nonhomotheticity of IT demand and find an elasticity of substitution between IT and non- IT inputs that falls below unity. Under the estimated model parameters, the cross-sectional predictions of the model match the observed relationship of firm size with IT intensity (positive) and labor share (negative). In addition, in response to the fall in the relative price of IT inputs in post-1990 France, the model explains about half of both the observed rise in market concentration and the market reallocations toward low-labor-share firms. |
| Keywords: | information technology, labor share, competition, production function, nonhomotheticity. |
| JEL: | E10 E23 E25 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:nse:doctra:g2020-14&r= |
| By: | Mr. Emre Balibek; Ian Storkey |
| Abstract: | Cash and debt management operations are part of the “transactional” functions of public financial management. It is critical that these functions are resilient to external disruptions, ranging from information and communication technology (ICT) system outages to natural disasters. This technical manual aims to provide guidance on the steps that government cash and debt management units can follow to develop and implement a practical business continuity plan that economizes the resources used. It also discusses the evolving nature of business disruption risks faced by cash and debt management over the last decade, including the COVID-19 pandemic, as well as risk mitigation solutions that have emerged. |
| Keywords: | Business continuity planning; business impact analysis; operational risk management; business disruption risks; cash and debt management; COVID-19; pandemic |
| Date: | 2021–09–21 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imftnm:2021/010&r= |